{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generative Adversarial Networks (GANs)\n",
    "\n",
    "So far in CS231N, all the applications of neural networks that we have explored have been **discriminative models** that take an input and are trained to produce a labeled output. This has ranged from straightforward classification of image categories to sentence generation (which was still phrased as a classification problem, our labels were in vocabulary space and we’d learned a recurrence to capture multi-word labels). In this notebook, we will expand our repetoire, and build **generative models** using neural networks. Specifically, we will learn how to build models which generate novel images that resemble a set of training images.\n",
    "\n",
    "### What is a GAN?\n",
    "\n",
    "In 2014, [Goodfellow et al.](https://arxiv.org/abs/1406.2661) presented a method for training generative models called Generative Adversarial Networks (GANs for short). In a GAN, we build two different neural networks. Our first network is a traditional classification network, called the **discriminator**. We will train the discriminator to take images, and classify them as being real (belonging to the training set) or fake (not present in the training set). Our other network, called the **generator**, will take random noise as input and transform it using a neural network to produce images. The goal of the generator is to fool the discriminator into thinking the images it produced are real.\n",
    "\n",
    "We can think of this back and forth process of the generator ($G$) trying to fool the discriminator ($D$), and the discriminator trying to correctly classify real vs. fake as a minimax game:\n",
    "$$\\underset{G}{\\text{minimize}}\\; \\underset{D}{\\text{maximize}}\\; \\mathbb{E}_{x \\sim p_\\text{data}}\\left[\\log D(x)\\right] + \\mathbb{E}_{z \\sim p(z)}\\left[\\log \\left(1-D(G(z))\\right)\\right]$$\n",
    "where $z \\sim p(z)$ are the random noise samples, $G(z)$ are the generated images using the neural network generator $G$, and $D$ is the output of the discriminator, specifying the probability of an input being real. In [Goodfellow et al.](https://arxiv.org/abs/1406.2661), they analyze this minimax game and show how it relates to minimizing the Jensen-Shannon divergence between the training data distribution and the generated samples from $G$.\n",
    "\n",
    "To optimize this minimax game, we will aternate between taking gradient *descent* steps on the objective for $G$, and gradient *ascent* steps on the objective for $D$:\n",
    "1. update the **generator** ($G$) to minimize the probability of the __discriminator making the correct choice__. \n",
    "2. update the **discriminator** ($D$) to maximize the probability of the __discriminator making the correct choice__.\n",
    "\n",
    "While these updates are useful for analysis, they do not perform well in practice. Instead, we will use a different objective when we update the generator: maximize the probability of the **discriminator making the incorrect choice**. This small change helps to allevaiate problems with the generator gradient vanishing when the discriminator is confident. This is the standard update used in most GAN papers, and was used in the original paper from [Goodfellow et al.](https://arxiv.org/abs/1406.2661). \n",
    "\n",
    "In this assignment, we will alternate the following updates:\n",
    "1. Update the generator ($G$) to maximize the probability of the discriminator making the incorrect choice on generated data:\n",
    "$$\\underset{G}{\\text{maximize}}\\;  \\mathbb{E}_{z \\sim p(z)}\\left[\\log D(G(z))\\right]$$\n",
    "2. Update the discriminator ($D$), to maximize the probability of the discriminator making the correct choice on real and generated data:\n",
    "$$\\underset{D}{\\text{maximize}}\\; \\mathbb{E}_{x \\sim p_\\text{data}}\\left[\\log D(x)\\right] + \\mathbb{E}_{z \\sim p(z)}\\left[\\log \\left(1-D(G(z))\\right)\\right]$$\n",
    "\n",
    "### What else is there?\n",
    "Since 2014, GANs have exploded into a huge research area, with massive [workshops](https://sites.google.com/site/nips2016adversarial/), and [hundreds of new papers](https://github.com/hindupuravinash/the-gan-zoo). Compared to other approaches for generative models, they often produce the highest quality samples but are some of the most difficult and finicky models to train (see [this github repo](https://github.com/soumith/ganhacks) that contains a set of 17 hacks that are useful for getting models working). Improving the stabiilty and robustness of GAN training is an open research question, with new papers coming out every day! For a more recent tutorial on GANs, see [here](https://arxiv.org/abs/1701.00160). There is also some even more recent exciting work that changes the objective function to Wasserstein distance and yields much more stable results across model architectures: [WGAN](https://arxiv.org/abs/1701.07875), [WGAN-GP](https://arxiv.org/abs/1704.00028).\n",
    "\n",
    "\n",
    "GANs are not the only way to train a generative model! For other approaches to generative modeling check out the [deep generative model chapter](http://www.deeplearningbook.org/contents/generative_models.html) of the Deep Learning [book](http://www.deeplearningbook.org). Another popular way of training neural networks as generative models is Variational Autoencoders (co-discovered [here](https://arxiv.org/abs/1312.6114) and [here](https://arxiv.org/abs/1401.4082)). Variatonal autoencoders combine neural networks with variationl inference to train deep generative models. These models tend to be far more stable and easier to train but currently don't produce samples that are as pretty as GANs.\n",
    "\n",
    "Here's an example of what your outputs from the 3 different models you're going to train should look like... note that GANs are sometimes finicky, so your outputs might not look exactly like this... this is just meant to be a *rough* guideline of the kind of quality you can expect:\n",
    "\n",
    "![caption](gan_outputs_pytorch.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "from torch.nn import init\n",
    "from torch.autograd import Variable\n",
    "import torchvision\n",
    "import torchvision.transforms as T\n",
    "import torch.optim as optim\n",
    "from torch.utils.data import DataLoader\n",
    "from torch.utils.data import sampler\n",
    "import torchvision.datasets as dset\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "def show_images(images):\n",
    "    images = np.reshape(images, [images.shape[0], -1])  # images reshape to (batch_size, D)\n",
    "    sqrtn = int(np.ceil(np.sqrt(images.shape[0])))\n",
    "    sqrtimg = int(np.ceil(np.sqrt(images.shape[1])))\n",
    "\n",
    "    fig = plt.figure(figsize=(sqrtn, sqrtn))\n",
    "    gs = gridspec.GridSpec(sqrtn, sqrtn)\n",
    "    gs.update(wspace=0.05, hspace=0.05)\n",
    "\n",
    "    for i, img in enumerate(images):\n",
    "        ax = plt.subplot(gs[i])\n",
    "        plt.axis('off')\n",
    "        ax.set_xticklabels([])\n",
    "        ax.set_yticklabels([])\n",
    "        ax.set_aspect('equal')\n",
    "        plt.imshow(img.reshape([sqrtimg,sqrtimg]))\n",
    "    return \n",
    "\n",
    "def preprocess_img(x):\n",
    "    return 2 * x - 1.0\n",
    "\n",
    "def deprocess_img(x):\n",
    "    return (x + 1.0) / 2.0\n",
    "\n",
    "def rel_error(x,y):\n",
    "    return np.max(np.abs(x - y) / (np.maximum(1e-8, np.abs(x) + np.abs(y))))\n",
    "\n",
    "def count_params(model):\n",
    "    \"\"\"Count the number of parameters in the current TensorFlow graph \"\"\"\n",
    "    param_count = np.sum([np.prod(p.size()) for p in model.parameters()])\n",
    "    return param_count\n",
    "\n",
    "answers = np.load('gan-checks-tf.npz')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset\n",
    " GANs are notoriously finicky with hyperparameters, and also require many training epochs. In order to make this assignment approachable without a GPU, we will be working on the MNIST dataset, which is 60,000 training and 10,000 test images. Each picture contains a centered image of white digit on black background (0 through 9). This was one of the first datasets used to train convolutional neural networks and it is fairly easy -- a standard CNN model can easily exceed 99% accuracy. \n",
    "\n",
    "To simplify our code here, we will use the PyTorch MNIST wrapper, which downloads and loads the MNIST dataset. See the [documentation](https://github.com/pytorch/vision/blob/master/torchvision/datasets/mnist.py) for more information about the interface. The default parameters will take 5,000 of the training examples and place them into a validation dataset. The data will be saved into a folder called `MNIST_data`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArEAAAJrCAYAAAD3f8tkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nu4g1DMMwDMMwIoddxBqGYRiGYRiR4/8A6z2B05APtBQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1a3ab99d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class ChunkSampler(sampler.Sampler):\n",
    "    \"\"\"Samples elements sequentially from some offset. \n",
    "    Arguments:\n",
    "        num_samples: # of desired datapoints\n",
    "        start: offset where we should start selecting from\n",
    "    \"\"\"\n",
    "    def __init__(self, num_samples, start=0):\n",
    "        self.num_samples = num_samples\n",
    "        self.start = start\n",
    "\n",
    "    def __iter__(self):\n",
    "        return iter(range(self.start, self.start + self.num_samples))\n",
    "\n",
    "    def __len__(self):\n",
    "        return self.num_samples\n",
    "\n",
    "NUM_TRAIN = 50000\n",
    "NUM_VAL = 5000\n",
    "\n",
    "NOISE_DIM = 96\n",
    "batch_size = 128\n",
    "\n",
    "mnist_train = dset.MNIST('./cs231n/datasets/MNIST_data', train=True, download=True,\n",
    "                           transform=T.ToTensor())\n",
    "loader_train = DataLoader(mnist_train, batch_size=batch_size,\n",
    "                          sampler=ChunkSampler(NUM_TRAIN, 0))\n",
    "\n",
    "mnist_val = dset.MNIST('./cs231n/datasets/MNIST_data', train=True, download=True,\n",
    "                           transform=T.ToTensor())\n",
    "loader_val = DataLoader(mnist_val, batch_size=batch_size,\n",
    "                        sampler=ChunkSampler(NUM_VAL, NUM_TRAIN))\n",
    "\n",
    "\n",
    "imgs = loader_train.__iter__().next()[0].view(batch_size, 784).numpy().squeeze()\n",
    "show_images(imgs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Noise\n",
    "Generate uniform noise from -1 to 1 with shape `[batch_size, dim]`.\n",
    "\n",
    "Hint: use `torch.rand`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def sample_noise(batch_size, dim):\n",
    "    \"\"\"\n",
    "    Generate a PyTorch Tensor of uniform random noise.\n",
    "\n",
    "    Input:\n",
    "    - batch_size: Integer giving the batch size of noise to generate.\n",
    "    - dim: Integer giving the dimension of noise to generate.\n",
    "    \n",
    "    Output:\n",
    "    - A PyTorch Tensor of shape (batch_size, dim) containing uniform\n",
    "      random noise in the range (-1, 1).\n",
    "    \"\"\"\n",
    "    return torch.Tensor(batch_size, dim).uniform_(-1, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make sure noise is the correct shape and type:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All tests passed!\n"
     ]
    }
   ],
   "source": [
    "def test_sample_noise():\n",
    "    batch_size = 3\n",
    "    dim = 4\n",
    "    torch.manual_seed(231)\n",
    "    z = sample_noise(batch_size, dim)\n",
    "    np_z = z.cpu().numpy()\n",
    "    assert np_z.shape == (batch_size, dim)\n",
    "    assert torch.is_tensor(z)\n",
    "    assert np.all(np_z >= -1.0) and np.all(np_z <= 1.0)\n",
    "    assert np.any(np_z < 0.0) and np.any(np_z > 0.0)\n",
    "    print('All tests passed!')\n",
    "    \n",
    "test_sample_noise()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Flatten\n",
    "\n",
    "Recall our Flatten operation from previous notebooks... this time we also provide an Unflatten, which you might want to use when implementing the convolutional generator. We also provide a weight initializer (and call it for you) that uses Xavier initialization instead of PyTorch's uniform default."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class Flatten(nn.Module):\n",
    "    def forward(self, x):\n",
    "        N, C, H, W = x.size() # read in N, C, H, W\n",
    "        return x.view(N, -1)  # \"flatten\" the C * H * W values into a single vector per image\n",
    "    \n",
    "class Unflatten(nn.Module):\n",
    "    \"\"\"\n",
    "    An Unflatten module receives an input of shape (N, C*H*W) and reshapes it\n",
    "    to produce an output of shape (N, C, H, W).\n",
    "    \"\"\"\n",
    "    def __init__(self, N=-1, C=128, H=7, W=7):\n",
    "        super(Unflatten, self).__init__()\n",
    "        self.N = N\n",
    "        self.C = C\n",
    "        self.H = H\n",
    "        self.W = W\n",
    "    def forward(self, x):\n",
    "        return x.view(self.N, self.C, self.H, self.W)\n",
    "\n",
    "def initialize_weights(m):\n",
    "    if isinstance(m, nn.Linear) or isinstance(m, nn.ConvTranspose2d):\n",
    "        init.xavier_uniform(m.weight.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CPU / GPU\n",
    "By default all code will run on CPU. GPUs are not needed for this assignment, but will help you to train your models faster. If you do want to run the code on a GPU, then change the `dtype` variable in the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#dtype = torch.FloatTensor\n",
    "dtype = torch.cuda.FloatTensor ## UNCOMMENT THIS LINE IF YOU'RE ON A GPU!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Discriminator\n",
    "Our first step is to build a discriminator. Fill in the architecture as part of the `nn.Sequential` constructor in the function below. All fully connected layers should include bias terms. The architecture is:\n",
    " * Fully connected layer from size 784 to 256\n",
    " * LeakyReLU with alpha 0.01\n",
    " * Fully connected layer from 256 to 256\n",
    " * LeakyReLU with alpha 0.01\n",
    " * Fully connected layer from 256 to 1\n",
    " \n",
    "Recall that the Leaky ReLU nonlinearity computes $f(x) = \\max(\\alpha x, x)$ for some fixed constant $\\alpha$; for the LeakyReLU nonlinearities in the architecture above we set $\\alpha=0.01$.\n",
    " \n",
    "The output of the discriminator should have shape `[batch_size, 1]`, and contain real numbers corresponding to the scores that each of the `batch_size` inputs is a real image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def discriminator():\n",
    "    \"\"\"\n",
    "    Build and return a PyTorch model implementing the architecture above.\n",
    "    \"\"\"\n",
    "    model = nn.Sequential(Flatten(),\n",
    "                          nn.Linear(784, 256),\n",
    "                          nn.LeakyReLU(negative_slope=0.01, inplace=True),\n",
    "                          nn.Linear(256, 256),\n",
    "                          nn.LeakyReLU(negative_slope=0.01, inplace=True),\n",
    "                          nn.Linear(256, 1))\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test to make sure the number of parameters in the discriminator is correct:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct number of parameters in discriminator.\n"
     ]
    }
   ],
   "source": [
    "def test_discriminator(true_count=267009):\n",
    "    model = discriminator()\n",
    "    cur_count = count_params(model)\n",
    "    if cur_count != true_count:\n",
    "        print('Incorrect number of parameters in discriminator. Check your achitecture.')\n",
    "    else:\n",
    "        print('Correct number of parameters in discriminator.')     \n",
    "\n",
    "test_discriminator()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generator\n",
    "Now to build the generator network:\n",
    " * Fully connected layer from noise_dim to 1024\n",
    " * ReLU\n",
    " * Fully connected layer with size 1024 \n",
    " * ReLU\n",
    " * Fully connected layer with size 784\n",
    " * TanH\n",
    "   * To clip the image to be [-1,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def generator(noise_dim=NOISE_DIM):\n",
    "    \"\"\"\n",
    "    Build and return a PyTorch model implementing the architecture above.\n",
    "    \"\"\"\n",
    "    model = nn.Sequential(nn.Linear(noise_dim, 1024),\n",
    "                          nn.ReLU(inplace=True),\n",
    "                          nn.Linear(1024, 1024),\n",
    "                          nn.ReLU(inplace=True),\n",
    "                          nn.Linear(1024, 784),\n",
    "                          nn.Tanh())\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test to make sure the number of parameters in the generator is correct:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct number of parameters in generator.\n"
     ]
    }
   ],
   "source": [
    "def test_generator(true_count=1858320):\n",
    "    model = generator(4)\n",
    "    cur_count = count_params(model)\n",
    "    if cur_count != true_count:\n",
    "        print('Incorrect number of parameters in generator. Check your achitecture.')\n",
    "    else:\n",
    "        print('Correct number of parameters in generator.')\n",
    "\n",
    "test_generator()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GAN Loss\n",
    "\n",
    "Compute the generator and discriminator loss. The generator loss is:\n",
    "$$\\ell_G  =  -\\mathbb{E}_{z \\sim p(z)}\\left[\\log D(G(z))\\right]$$\n",
    "and the discriminator loss is:\n",
    "$$ \\ell_D = -\\mathbb{E}_{x \\sim p_\\text{data}}\\left[\\log D(x)\\right] - \\mathbb{E}_{z \\sim p(z)}\\left[\\log \\left(1-D(G(z))\\right)\\right]$$\n",
    "Note that these are negated from the equations presented earlier as we will be *minimizing* these losses.\n",
    "\n",
    "**HINTS**: You should use the `bce_loss` function defined below to compute the binary cross entropy loss which is needed to compute the log probability of the true label given the logits output from the discriminator. Given a score $s\\in\\mathbb{R}$ and a label $y\\in\\{0, 1\\}$, the binary cross entropy loss is\n",
    "\n",
    "$$ bce(s, y) = y * \\log(s) + (1 - y) * \\log(1 - s) $$\n",
    "\n",
    "A naive implementation of this formula can be numerically unstable, so we have provided a numerically stable implementation for you below.\n",
    "\n",
    "You will also need to compute labels corresponding to real or fake and use the logit arguments to determine their size. Make sure you cast these labels to the correct data type using the global `dtype` variable, for example:\n",
    "\n",
    "\n",
    "`true_labels = Variable(torch.ones(size)).type(dtype)`\n",
    "\n",
    "Instead of computing the expectation, we will be averaging over elements of the minibatch, so make sure to combine the loss by averaging instead of summing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def bce_loss(input, target):\n",
    "    \"\"\"\n",
    "    Numerically stable version of the binary cross-entropy loss function.\n",
    "\n",
    "    As per https://github.com/pytorch/pytorch/issues/751\n",
    "    See the TensorFlow docs for a derivation of this formula:\n",
    "    https://www.tensorflow.org/api_docs/python/tf/nn/sigmoid_cross_entropy_with_logits\n",
    "\n",
    "    Inputs:\n",
    "    - input: PyTorch Variable of shape (N, ) giving scores.\n",
    "    - target: PyTorch Variable of shape (N,) containing 0 and 1 giving targets.\n",
    "\n",
    "    Returns:\n",
    "    - A PyTorch Variable containing the mean BCE loss over the minibatch of input data.\n",
    "    \"\"\"\n",
    "    neg_abs = - input.abs()\n",
    "    loss = input.clamp(min=0) - input * target + (1 + neg_abs.exp()).log()\n",
    "    return loss.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def discriminator_loss(logits_real, logits_fake):\n",
    "    \"\"\"\n",
    "    Computes the discriminator loss described above.\n",
    "    \n",
    "    Inputs:\n",
    "    - logits_real: PyTorch Variable of shape (N,) giving scores for the real data.\n",
    "    - logits_fake: PyTorch Variable of shape (N,) giving scores for the fake data.\n",
    "    \n",
    "    Returns:\n",
    "    - loss: PyTorch Variable containing (scalar) the loss for the discriminator.\n",
    "    \"\"\"\n",
    "    N, _ = logits_real.size()\n",
    "    loss = (bce_loss(logits_real, Variable(torch.ones(N)).type(dtype)) +\n",
    "            bce_loss(logits_fake, Variable(torch.zeros(N)).type(dtype)))\n",
    "    return loss\n",
    "\n",
    "def generator_loss(logits_fake):\n",
    "    \"\"\"\n",
    "    Computes the generator loss described above.\n",
    "\n",
    "    Inputs:\n",
    "    - logits_fake: PyTorch Variable of shape (N,) giving scores for the fake data.\n",
    "    \n",
    "    Returns:\n",
    "    - loss: PyTorch Variable containing the (scalar) loss for the generator.\n",
    "    \"\"\"\n",
    "    N, _ = logits_fake.size()\n",
    "    loss = bce_loss(logits_fake, Variable(torch.ones(N)).type(dtype))\n",
    "    return loss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test your generator and discriminator loss. You should see errors < 1e-7."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum error in d_loss: 0\n"
     ]
    }
   ],
   "source": [
    "def test_discriminator_loss(logits_real, logits_fake, d_loss_true):\n",
    "    d_loss = discriminator_loss(Variable(torch.Tensor(logits_real)).type(dtype),\n",
    "                                Variable(torch.Tensor(logits_fake)).type(dtype)).data.cpu().numpy()\n",
    "    print(\"Maximum error in d_loss: %g\"%rel_error(d_loss_true, d_loss))\n",
    "\n",
    "test_discriminator_loss(answers['logits_real'], answers['logits_fake'],\n",
    "                        answers['d_loss_true'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum error in g_loss: 3.86398e-08\n"
     ]
    }
   ],
   "source": [
    "def test_generator_loss(logits_fake, g_loss_true):\n",
    "    g_loss = generator_loss(Variable(torch.Tensor(logits_fake)).type(dtype)).data.cpu().numpy()\n",
    "    print(\"Maximum error in g_loss: %g\"%rel_error(g_loss_true, g_loss))\n",
    "\n",
    "test_generator_loss(answers['logits_fake'], answers['g_loss_true'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Optimizing our loss\n",
    "Make a function that returns an `optim.Adam` optimizer for the given model with a 1e-3 learning rate, beta1=0.5, beta2=0.999. You'll use this to construct optimizers for the generators and discriminators for the rest of the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_optimizer(model):\n",
    "    \"\"\"\n",
    "    Construct and return an Adam optimizer for the model with learning rate 1e-3,\n",
    "    beta1=0.5, and beta2=0.999.\n",
    "    \n",
    "    Input:\n",
    "    - model: A PyTorch model that we want to optimize.\n",
    "    \n",
    "    Returns:\n",
    "    - An Adam optimizer for the model with the desired hyperparameters.\n",
    "    \"\"\"\n",
    "    optimizer = optim.Adam(model.parameters(), lr=1e-3, betas=(0., 0.999))\n",
    "    return optimizer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training a GAN!\n",
    "\n",
    "We provide you the main training loop... you won't need to change this function, but we encourage you to read through and understand it. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def run_a_gan(D, G, D_solver, G_solver, discriminator_loss, generator_loss, show_every=250, \n",
    "              batch_size=128, noise_size=96, num_epochs=10):\n",
    "    \"\"\"\n",
    "    Train a GAN!\n",
    "    \n",
    "    Inputs:\n",
    "    - D, G: PyTorch models for the discriminator and generator\n",
    "    - D_solver, G_solver: torch.optim Optimizers to use for training the\n",
    "      discriminator and generator.\n",
    "    - discriminator_loss, generator_loss: Functions to use for computing the generator and\n",
    "      discriminator loss, respectively.\n",
    "    - show_every: Show samples after every show_every iterations.\n",
    "    - batch_size: Batch size to use for training.\n",
    "    - noise_size: Dimension of the noise to use as input to the generator.\n",
    "    - num_epochs: Number of epochs over the training dataset to use for training.\n",
    "    \"\"\"\n",
    "    iter_count = 0\n",
    "    for epoch in range(num_epochs):\n",
    "        for x, _ in loader_train:\n",
    "            if len(x) != batch_size:\n",
    "                continue\n",
    "            D_solver.zero_grad()\n",
    "            real_data = Variable(x).type(dtype)\n",
    "            logits_real = D(2* (real_data - 0.5)).type(dtype)\n",
    "\n",
    "            g_fake_seed = Variable(sample_noise(batch_size, noise_size)).type(dtype)\n",
    "            fake_images = G(g_fake_seed).detach()\n",
    "            logits_fake = D(fake_images.view(batch_size, 1, 28, 28))\n",
    "\n",
    "            d_total_error = discriminator_loss(logits_real, logits_fake)\n",
    "            d_total_error.backward()        \n",
    "            D_solver.step()\n",
    "\n",
    "            G_solver.zero_grad()\n",
    "            g_fake_seed = Variable(sample_noise(batch_size, noise_size)).type(dtype)\n",
    "            fake_images = G(g_fake_seed)\n",
    "\n",
    "            gen_logits_fake = D(fake_images.view(batch_size, 1, 28, 28))\n",
    "            g_error = generator_loss(gen_logits_fake)\n",
    "            g_error.backward()\n",
    "            G_solver.step()\n",
    "\n",
    "            if (iter_count % show_every == 0):\n",
    "                print('Iter: {}, D: {:.4}, G:{:.4}'.format(iter_count,d_total_error.data[0],g_error.data[0]))\n",
    "                imgs_numpy = fake_images.data.cpu().numpy()\n",
    "                show_images(imgs_numpy[0:16])\n",
    "                plt.show()\n",
    "                print()\n",
    "            iter_count += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well that wasn't so hard, was it? In the iterations in the low 100s you should see black backgrounds, fuzzy shapes as you approach iteration 1000, and decent shapes, about half of which will be sharp and clearly recognizable as we pass 3000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter: 0, D: 1.378, G:0.6873\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xm4V2X1N/4FAqIoIjgjOICRgBOKOWCOiPOQCmZoT2ZO\n5ayZpqlphuaQoX3LeU5TzFJDE2ecRxRNIclAEDBwSsBEPs8fXK+199kHk/NcXdfv+zvu9c/hHD6f\nve9pr/d7vde6792m0WhEbbXV9v9/a/v/dQNqq622/47VD3NttbUSqx/m2mprJVY/zLXV1kqsfphr\nq62VWP0w11ZbK7H6Ya6ttlZi9cNcW22txOqHubbaWom1a8mHDzzwwEZExIMPPuj3iIj45JNPIiLi\n3Xffjb59+0ZExNNPPx0RERtttFFERKywwgoREdGlS5eIiDj66KMjImL77bdv8ve//OUvsdNOO0VE\nxKeffhoREWussUZERDz11FMREfH1r389IiL+/e9/R0TE0ksvHRER9913X0REdOjQISIiBg4cGI88\n8khERLz99tsREbHllltGRMSkSZMiIuKxxx5ro39nnnlmIyJi9uzZERGx0korRURkn6ZMmZLt/POf\n/xwREXvvvXdERIwZMyYiIo488siIiPjhD38YERH9+vVr0taPPvoodt1114iImDdvXkREtG3btsk4\nzp07NyIilltuuYiIePjhhyMiYs6cOU2u+c1vfjOOOeaYiIho127hVO67774REbHkkktGRMT++++f\n/Yso5nDKlCkREXHUUUdluyIiGo1GqAqcNm1a/i2imMt//vOfERHxxz/+MSIivve97zUZ0xtvvDFO\nOumkiIh44IEHIiJi5syZERE5tx9//HFERCy//PJNxuKll16KiIi33norIiIOP/zwuPfeeyOiWHeD\nBw8udylGjhyZfdx6660bERE9evSIiGIOV1555bzvMsssExERSy21VEQUa/O9996LiIhll102Ihau\nxXLbt9tuu4iImDFjRs7BBx98EBHFHA0cODAiInr27BkREZMnT46IiDZtFjbx2WefjYiIbbfdNiIW\nzttrr73WZPz22GOPJr9fcMEFTebw86xFD/POO+8cEcWCOeeccyIi4hvf+EZELHyYn3vuuYiIWHHF\nFSMi4m9/+1tEFAPlwVtnnXUiIuL73/9+REQccsghERFx0EEHxTvvvBMRxSLyQA4YMCAiisE28a45\nY8aMiCgevk8//TQfkOuvvz4iIttnMMu29tprR8TChyQi4vXXX4+IiLFjx0bEwonbZ599IiLia1/7\nWkQUD7ExsHjbt28fEREbbLBBREQ8+uijERGx++67Zzu32WabiIg47LDDIiLil7/8ZUREPPTQQzme\nEcWCcM+OHTtGxMIH0iI944wzmrT586x79+4REdGnT5+IKBYMW2qppWKVVVaJiIivfOUrERFx4YUX\nRkTE1KlTI6J4IC1QD8c111wTEQsfwNtvvz0iItZbb72IiPjwww8jIuLNN9+MiGIu58+f3+Ta5nyH\nHXaIiIUPte/ccMMNERH5cOtL2azJcePGRUQBEhxT165dY/PNN4+IwoFxEvr7yiuvRETE+PHjIyLi\nvPPOi4iI3//+9xGxcN6011ysu+66EVE4p1mzZkVExG677RYREbfccktEFA5BezbbbLN8mE8++eQm\nY8QhLK7VNLu22lqJtWnJRouhQ4c2IiK6desWEQWdfeaZZyIion///olIvXr1ioiIn/70pxERsf76\n60dExFZbbRURBa1CKf/1r39FxELE6Nq1a0RE3H333RFRIC+U582hJDq01157RURBt1dbbbX8Liq7\n2mqrRURBS0899dSkMDfeeGMjokB43vVXv/pVREScfvrpMX369Cb900bIjKK7vp/avvbaa+dYQHHf\ngZKoGiqs7f379292bWPw5JNPNhnPiRMnRkTEWWed1YSiXXjhhY2Iguaah//5n/+JiIWoi/lsuOGG\nEVGwjyWWWCLK38XUhBy+t8cee+T4XHHFFRFRsCUsy7W+/e1vR0TE448/HhERq6++ekQU62GZZZZJ\ndvOHP/whIgpabK2dcsopzeYQMhtDYccSSyyRjMfYvfDCCxFRMCXz4Dv6J8xYccUVk8bfeOONERGx\nySabREQReugX9oBef/bZZ03a3rNnz9h0000jomAI1gqmcOyxxy4Wza6RubbaWom1KGYmSPHU4oUf\n//jHERFx3XXXRadOnSKiQM9ddtklIgqPywPzbEOGDImIIi5bb7310nutueaaEVF4qksuuSQiollc\n3rlz54goPClPPmPGjBSeCBa8urirbDwwNPfZq666KiIWIj5Pj2EQ1N5///2IKIS/3XffPSKK2BBy\nDhgwIMUd/YBip556akQUiC1GhMjiSDHVBhtskChDHNxxxx0jIuKuu+5q1r+IyFgWGhHjDj300OzX\nE088ERGFaCQmNi60BXbiiSdGRMSZZ54ZEQtRyFrRf/f9yU9+EhGFmAex77zzzogoYkxINnfu3Pjd\n734XEUUM6f7WWNmMHe0AW8MaXn/99YzjrZsFCxZERIGMGKfPHXTQQRFRjGmvXr2SOVij0JwGJC53\nX/NvvLGMadOmZczsvltvvXVERLLAxbUamWurrZVYi5AZ/yfHU0QpewcccEDK/byN+IryzKv+4x//\niIiIE044ISIKDzpt2rREIikBsdvVV18dEUVMKXaE0GJPSuESSyyRCrBYBlKIccsGXcUz2kQRX3nl\nldPzjh49OiIK1kAZ5VXvv//+iCgQ4vLLL4+Ihazm5ZdfjoiCrYi3brvttogo4nrq9sEHHxwREWut\ntVZERH7/lFNOSRXb+EKryy67rFn/Igq11f/LKlBwu3XrlqwCEhlnGoKUGbQxFr4XUajSGMBxxx0X\nERF33HFHRBSM5he/+EVEFEo9hKZ+9+jRI1NR7gMVt9hii0X2MaKI57GrVVddNfuL+RkzbBISGv/H\nHnssIgodAhtr27ZtrklzYRxlLVzDfEiRQX9rasGCBalb0J58R5pzca1FD7OUhYkgt5u48ePH5wMh\nnYJGoRfSF9JPaDAq9/HHH+cDQIjyoKCZN910U5PfPdxEDw9zv379kpIOHTo0IgoBxmeGDRuW/RMS\nCB+uvPLKiCjoWJcuXeKCCy6IiOKhQHPRQ5TQdT0IKPP777+fwovxs6g4EZQNRfOwo2FSZYceemgu\nTGELCi9kQBHZAQccEBGFqIbu+f2pp57KPLL7myP5/V//+tcREdG7d++IKNIyQpA333wzTjvttIgo\nBCLUHf2WfjOHFr8FrS6gXbt2sfHGG0dEAQQ+I8deNmGGh6f6QE6cODFptXkmuAKR6667LiKKB9S6\n9wDOmjUr55UT9Fnrn6NTIwEIrTvzs9xyy6Vj0L+///3vTT4zaNCgZv1clNU0u7baWom1CJlRJh6Y\nQZS5c+emByJEQAwUiSd+9dVXI6KgOLzhtttum6ICj/TXv/61yX3+z//5PxERcfPNN0dEIVRIx+y3\n334RsRBZpKnQ/2phSdl4bD/Rdkg4c+bMRANshBclDn33u9+NiKJIRXXU6aefHhELK658F23mzXlt\nqAahq8KcNiy//PJZjCOtIrz505/+FBHNkZmo5V7mSapo5513zpQIdDQfzz//fEREnH322RFRUGYI\nfu2110bEQjpqnIVZxpI4iYlBMGaesJd58+bld/VfX4UlqgkjilDAvBBrpVO33nrrRFWfgdC+a90J\n86D68ccfHxELQwMFM+i7uUTFhZ7WOYZIiBUePfzww/HGG29ERFHIJIzRnsW1Gplrq62VWIuQmcfg\nqcVZvPp6662XyDB8+PCIKIJ53lVcwnOJKXjBr33taxnvEKugPXGBV3cNPwlWEGSllVZKj8iraw/R\noWyKQ/zUXymvAw88ML0ocYp+cPHFF0dEEXf7u5hW3HXfffclk5BqUXIIpRTBHHHEERFR1K+LZSHn\n7NmzE+mMn9gTclTt0ksvjYgCIb/1rW9FRMFYOnbsmGkuaUNipbHElBQ7GCcptj59+mR7CF+uSUuB\n+sbTWEBJsfygQYOSkUE/zBCylg3DI1QSGbG2zz77LNOH5tC6ol3QJqxl9fd0lzfffDOZDaFN26wd\n4pxxtWatvwkTJkTEwnlwf6zEOPp9ca1G5tpqayXWImTmZSiiYgko8MILLyRa89piFd6Qcsj7UQPF\nlrfeemvGWRTwaowu7uBtqZ0Qzr2WXHLJVJWlEKrpnbJV487DDz88IgpUufPOO1PFFh+6p5RUtbwS\nqhizJZZYIlVyeoHvKjQQz9MGIDHUoqC3b98+0Um6Rrzv2lXDkMS55k5G4K233oqvfvWrERH5k1Kr\n0MNGGxsQsBybHB566KFMBWIkWBYF3Jwee+yxERExatSoiChQ31y8//772UYqdnW3XNnErJDf2nD/\nd955J5HPxgnrCVvBbpTdWk/lrAl2pU2Q2vxjIK6hCEZftP3ZZ59NFlctWtE+6/CLrEbm2mprJdYi\nZIYuUIfnoPJ98MEHGaPI51JuxdliISgPfRTkr7vuulnQroySV1UAAFXERe516623RkRR5C4/HVGo\ny5RgaFc2TIBXHTFiREQUpaazZs3KGEnOUf/EuZT0/fffv0m/of2GG26Y42WrJXXVtSAFZZxiLb8L\noY877rhEDbGpn8awagow5HvvueeeiCiKNx5++OFEXjEbBkRdFWu6hvE2xgMGDIgf/ehHEVGsDVbd\nAim2xuAgMwbVqVOn1B3OP//8iCjQ3HosG0VYMY/iHds2V1pppYxnsRk1D5RnrA3LwTblygcOHJjs\nSSGTdYyteg6wLfl/GRhjvMMOO2RpsW3AL774YkQUutPiWo3MtdXWSqxFyAxdlL3xgqps3nrrrWZF\n6jyXWFncJbcq5oNga665ZpaLiivEWTyjon2loDw31IT6q6++eua3oQrlXSxbNqo4Tyw+lrOdPn16\nelEIJ9bXfsgov83ERW3btk31VzmsqiVxntyoNoqzjDdV+5577sk5Mb7GFcJVzT3lzvfcc8+IiDwZ\nZPPNN89xpqJrj3iUhgDBILcsxD333JPsQbxtnLAccT90FXPatGPMN9lkk2RztBRMBqKWTWWZMXZ/\nOfvZs2fn+Kmss41V+7EE8TBUt64+/PDDPLjAmlNSTJ3Xf4gsa6M0F3OYMGFCPk9U7er4L67VyFxb\nba3EWoTM4hsKtONueJJ9990366ohldgI6kE0nkoOU/wya9asVCDldyG1OApy2hJpW6VqHIg6ZMiQ\njI3djxLKs5ZNHFONvf1+8MEHp/d0T54ZAsiJqyIyNvLr8+fPTzbiO+IoR8oYK+qpKi1oC83atWuX\nddF0AxtIoHzVxIXGCPuh8G6wwQa5NZPqTq2GaDZUUPIhtRr23XffPcfd/6kWs6ECCkJdOghEpnYP\nHDgw2ZS2UtmtmbJR65l5kH8eMmRIxu3YietjLWqlzRNtCDNZZZVVsu/yxdZDNe+PVYmDsUg1EREF\nilvnWC2Wu7hWI3NttbUSaxEyU055MnGhGOP3v/99xm62ssnZiWF4fV6WR+YFX3nllUQCqjlVkben\nOouheFR1x/J148ePzximugVNjXjZqIn6o/aXMv3iiy8mOkIy/bMDCkKqrxYblhEHwxDvykViMe6h\njT5HGYUUhxxySPzmN7+JiCIWo6o7HbRqNAR5XIiphv6SSy7JumE7xCj0Pmt8ZAYgOCY1ffr0jFHF\nsOI/TMLaUYFmXiCpOHzq1Km5ppg1tCjFHhJab/qLNdx111053tYXJBTfYp6Ymd1MasCXWGKJZifB\n2lHGILO/03lkYOgNf/vb3zLrQgE339bJ4lqNzLXV1kqsRcgsDuZ1eFEK6iqrrJLxLM8ovoFYvCll\nkJf3ve9973vp6R2jA93EJfKx8qAQGqKpOlqwYEEqlmJIXp7Hdo+IiJ///OcRUcRxPLK2brLJJon+\nUEgMLo6FGuJg96PS3nvvvZmLFDNDeXltSFGtIjKmmMndd9+dMbuYnNlH7JoMIovPqrXF/fv3T1SU\n74Y+0JupajLG5ni11VbLWBmq0xLkyiG18dRXOXX6x9ixY1O9pnjLblgzZaONqAOoHqDRsWPHXMey\nBdaLXYFQHFs0x67ZsWPHXBvGxjybd0wJq4TQYvpydRmtRMZF3/Vlca1FD7OyQydQoFCS8LNnz86B\nNjAoBAqLTvkOR6AgYIsttkiZXzrDAeOooy2BzOSUD6uPWPhQegAIDwreq0JJRHEuGGFFUYTrtWvX\nLqmX8648iE6F0FZpM9/1INx2222ZpnKgAQfg3GSOgvBlMXEqrtm7d++8P1prcXmwqubaTF/N07hx\n49IBe1ikgDgZYZCxtEFB6uyKK67IkIHTsFAJoB4up7cSxqRpCEv9+/fPzxKdhBkcRdk8ZADHQ6Yv\na6+9dv7b5hig5AEjjI0cOTIiijlVCHPwwQenQzWXQjKFPpwT4YuYySEYw9122y2dhmfBT+WxHO4X\nWU2za6utlViLzs2+7rrrGhGF1+PlpV/22GOPpHfoEw8GqRlvD4WJa1tuuWUigLQVUYeEDzlQRmKC\na/DOb731VnpbVBzKSU+MHj069wpecsklTQZDG/Wlffv2yQKk4L7zne9ERHHuNKTT1qrgt/fee2f7\niChQG7qihlgO8UzBjWsRTCIKdkJ4VPp67rnnNtkL6VxphT7SgEKWWbNm5X2gNcQ1vkQ/6EM4wna2\n2267vL9Uni2OxCXbComa0M/aMk/z58/PTSPELSgPdUeMGJF9dC64tYld6V+bNm2S2VhfRCnFMcaE\nqOn+1vAxxxyT7TY3xEnf0T9sSmFKlSmuv/762Q9ryu/Cil//+tf1udm11fZlshbFzJBE3CNFRUCY\nO3duemBxgJI4py2WPW5EITZAlt69e2fsutlmm0VE4akk8xXPQ0FxorJI9+7Ro0cW//OkYhz3LRuB\nTfme/vHMffr0SWFHnGjrHrYgdiJI/eAHP4iIYtN6jx49cqOAF4SJG6V6IJ740YEH+kKY6ty5c8Zx\nkMh2OZ6/auJBoguWIIX33HPP5dhUC08gNgTWPkgGuWbPnp2I5DPKF8X4kNgBiBgUNuJ77du3j1NO\nOSUiCkFICao1UzZFMcYYA8OUxo0bl21TOFONWW36UQCizYS4CRMmNCvblM7DYoyRn65hLRF1O3bs\nmIdpYJjEVG1fXKuRubbaWom1CJkhIyQWK5UPPqMo83ZiRoocRZrnFP9JjUCliAIJpD6gO2SS2qmi\nvljyySefjIsuuigiim174lKfLRvG4bpSSFD4j3/8Y3pNrAASQCdxZfValOrbb789r6E4QHEGBVq6\nToqIagy9sJpx48YlqhtvY/F5b4PEcijEvD8msWDBgozZtR3KQyFxubdgQDj6y9y5c7NcVowoLjXf\n5tnxyK6NOVhjbdq0yfsZw+qaKZt1JkVUVZE//PDDXE8YCGSkatsMQpEXb2OACxYsSEZDe/B6Y2Mg\nVrfOjINrGLM2bdpkURKD3tJbi2s1MtdWWyuxFiEzb09VhBzlo3blB3lESEXNs9WOQiwusZlhtdVW\nS28NGVzDEUBiGoUHDsUXM1MUO3funGoqhVxZp5itbHKCVGwoJmZdsGBBxsxiHj+pt/LNvLrjhRRD\nbLDBBokaUER/IbLcLM1A7Gqs5Lqvueaa9PzlQ+PLP6smzlRgYx70a9ttt002Vd0KaOwwNIitP+LD\nXXfdNdEMimJINtxDMNkMjA6CmrdvfOMbqV1U3zBSZnFMbl6ZMAalv507d875NXdYBPXYnMlHY6AY\nUq9evbLoCHuzvrEa2lE1RqZ6yyEPGTIkURtj0C/tssHji6xG5tpqayXWImTmbXgQcQGPPWfOnKzK\nsV1O3Atlqxsr5Pwg24cffpg5YYggRoY2FGk5bYhFGXWvmTNn5nWp2Tw31bRsFEeIJJaCBBtttFHG\nSvqOJShX5IEppuJcKvc//vGPVLip8hgGFMGA/L+3LDomF6LfcsstibTmQA62WvjPKM6qqcyPWHvj\njTdORuKaUBa7wLowM4xIFmLFFVds9pIBGQIsCyNQTQjBIShUvO+++zKetvUSi1gUYmlrVbuBxoMG\nDcr2yg5QoKGodaBKy3pUEXbIIYck09Nen9Ev6wDai8cddKh98+fPT1THxGxokalYXKuRubbaWom1\nCJl5fRsReHPedamllsotbfKv4k0qsnhbJZB4SIz5/PPPJ/pB4uohaRBM7pJCyHOLx7p165aqIe8n\nH7uoHKXac0gIoVRCTZ06Nb26rYe2KYp7eGJ16xBS/6666qocC4oy5qFqCALy0CrseHMo1qFDh2wj\n9VeNu7hXTTzDrqqv4DHWb731Vubbjav8LvW4esSyGK+8qYUqDbHc1/G82uk7+uia2MrOO++cVVb6\njfWIw71hM6LIKoi5jaW9AOedd14q+NYzjcL6cT/oqv/W8h/+8IesJccaoLragerbOGkb+ot19ejR\nI/uFcVibDrS0Lr/IamSurbZWYi1CZjXS4h/ejvfr0qVLxhAUT0qznJ6YBrryOhTxNdZYI/+GAfgO\nlRFi8IYUUebam266ab5KVfwnhuZ1yyZnq/aYesqrdujQIbf9eXWMTedVE6tVj0Daaaed0qvbQQZp\ntFX/bBeE3BR/20jbtm2bNeHVw/g/z8TMdAFbQO1EWm+99RJNoT0tgt4h/sQwtFM+/p577skX1kFg\n8+9alHB6h0yFvK2syIQJE5odeu9oJPF+2bAZqrHthOLfddddNw8lcOyVNqkZkBnAyKrv5F5//fWz\nnp6uYk6Mo/Wsdt+acm9ju/rqq+c1qrvSFnWAxn+yGplrq62VWIuQufriaOgjLv3www+zflt8pxKK\nFxerQVOxkthy8uTJzY56UZ2kQkp8Byl4Q9eAHM8880y2uRqrL+qAcXGv2l/fhZyPPvpoIocYUGxX\nPcAPUqru+u1vfxsRC9FFjhvDkb/0WZoBTy3OVClEkR84cGC2ERJoK+2iatoFmc2h759wwgl5fYc1\nOOqnetSuenSo6oDFXr16ZR8dDm/O6ATaiTHZB4xZyCC0b98+kQvKYn80hrJBTNkGyrQYvmfPnsmI\nMCHZAdcXB6u/9oIA/z937txme75dg1YhZq7umqKduMdyyy2XGo8xgt6Y7+Jajcy11dZKrEXIzDNT\nquWIxV1jx45NhRtiyDdDWZ5SdQt1T4y08847Z8zLu1fzfmp1oU+1Msn3x40bl3leaCJOEt+VTZyn\nogk6QN3+/funNxdXqt6Sc63G72eddVZEFMhzwAEH5Hf8POqooyKiiD3Fkf7Oc8uNyx5cc801zark\nxJOLOiA+okAQKquxwqRWWWWVZCbmBKuCbmJ4ca/Py4Ovu+66OR6qp1wDG6Eoi4cpuMYPgt9www2p\nEPsbluXVOjIMEUUcXT5kPqKYww4dOmS8Cl3tllLXYEeZOBdCu3///v2TgRlnuXf9VCugWs/4Vk/i\nueWWW3LOHAdsXWOiTqT5ImvRw2yLlgWgoTowY8aMXJA2EaAORAUPpsn08Otsv379UsTwfmAChXJL\nBfdKQ9FRC9rve+21Vy44bfQQL+r8KAKTSTPpNrF36dIl6TJqL12DdqNGKCcHpDBhjz32yLSVRUjI\nswnFQ+MsNAtF0YIH4Pvf/36mwsoltRFN37NVNqKiBSuFg5ai/BEFZbUAOWAUUjhAVDTX/fv3T3rp\ngXANR/WYW2GLYgvzZD2ss846uXY4huq7r8sm1elh0k+i4qxZs5LKc/DmEI0WenAawjxtW3311fNB\nM4fWszSX/qHMaLVUoHBn+PDhKby5jzmt389cW21fUmsRMvPIqCrPxhtOmTIl0UUxg4AfAhN5eB0o\nSpR45ZVXkt4qfYNykEGRgAP/IIQN7dDp3XffTQrFG/N60mllcx3X5W2VbG644YaJyNIG+o4iCT0g\nsp/G7tlnn82QA9VCDW0LNUYOGoCyRDu074477kgKBimgl4IIb5pkmBHTFki64oorJqvCwAiD+g4Z\n9ckYQ8ONN94400jGw2e8v5ioRcTEaCAYmzRpUt6H0GqtSPc51CGiEOu00dj6TvnABesMJddf6wdL\nsYYhds+ePTMVVQ09XEOYAW31CwuA+m+++WYyQe2onhq6uFYjc221tRJrETITT3gj4pVUwfDhw1NU\ngDqEAmIOtONlxSHis88++yxL3RSeVwtMiCUQSkxNoBNjrrXWWskiHP4nNUbAKhs0sSkCikHqv/71\nr3k8jLbZyE4rgNSQUWyu4Gby5MkpDhJPxHPiVsfkKJIxZsoNxeeffvppFuWITYln2EzVIASxR1EL\nVBg0aFCmmnxG3IeN6LvvYkzSkB988EGyCT/12X2gqTn82c9+FhHFMUv0mU022SQ31Fhb9AdoWzaC\nK+S3dqQtDzrooIzTjafrEFCrx0VVD1po27ZtIjx0xzCtY6iuNNQBHtawdbhgwYIcG/fzXXrG4lqN\nzLXV1kqsRUftDhs2rBFRSOVUOOVuZ511VsatYojq1i9IJd6pvid5gw02SMQSX0B5cdU111wTEYW6\nLT6igFJ7J02alMURVESoLk65+uqr8xjTY489thFRHA/My2IXEyZMyFgf4mgTb0pHEBMZXxrCp59+\nmgiMLYgreXvoJVbENCA4xGw0GhkjQxWMh3q8xx57NDmm9fLLL29yFK2YUuz62muvZZxvrlxbTGzs\nZDMgJ2Y0ceLE1Eh8RiGQ1JMiCjGucTRf3us9adKk7BNNA6rp4w9+8IPs4+mnn96IKLQAqrEY96KL\nLkqEt3FHbFo9fBJSQlNpro4dOybDcR/pTOyE0q6ISvqOYi6tFlGkVqtpLmOx884710ft1lbbl8la\nhMy11Vbb/16rkbm22lqJ1Q9zbbW1EmtRamqvvfZqRBQCiBpSaZEnnngiS/uIFOpqGWFIYQQRghh0\n9913p+AhFSD1JWVAKJCiIBTYWyzpv+uuu6ZQQeaXopDCOO2001JcOPLIIxsRhbBWfR3su+++m3+T\nHtJfp21IVTitQ7+UOt5www25k4gIVU0TEb6IJUTC6ts51lhjjRSSiGPGTL+vu+66JuLJVltt1Ygo\nCiGIQew0DOCtAAAgAElEQVSxxx5L0VJax3wQEaspG4KjAomnn346xUNrg6hnPKTUiD/6RGQyp+uu\nu26+A4ogR0w01uV3MR1//PGNiOZ7Aqy7bt26NXvZvf3lSn21ifDq8+Zh1KhR+eJ1++KNgc+ou5d2\nIohJixG5BgwYkLX2rqEk1Fo7//zzF0sAa9HDbKO5WmW10B7ubt26pXqo4kceloJrs7YGO0jda1rX\nXHPN3IKnAsqCpSq6lgVjAXiwfK5z5865qNXQWjQqdMpGLZWr9YBQqvfff/9UJy0WC5qSLgcrV+0a\nlP+rrroqN4pYaDIAPsNRUFU5Cg+eQxOnTJmSD5jtijQQWz2r5iHmODgID8+GG26Y7eJUOBsL0/87\nqMGh/u65//77p1rrO+ZM/tcRPB4GuXQPKgfSrVu3dM7WkrmTuy+bfK+shZoFD8/s2bMTaKp1Bbb2\nWlfUe063vDfAenU/bdl0000jogApDs6c+3z53cuyB7ZaAh5jsbhW0+zaamsl1iJkhhDqgNEPh9tt\nsMEG6ZHQDZVQPstj81goLATr1q1bDB06NCIKGmRrIs8vn8mj+budNzxohw4d4uyzz46IiJ/85CcR\nUVQcLcp4Ql5WGx0h+8EHH2RO0mHnxgI1s+NLdZE2yku/8MILibz6Bwl8BiWFCCi6HDdUmDFjRm47\nVEknJIG0VdN+15RDLm93NI5obbU9KqZUiqGnxuTtt9/OmnC7pDAWrE7IZIxdE8Uv15oLS+xYs+3T\nd8tm3alSlMNXV37EEUck0vssFgnNvUQBmmMPWN20adOSmmNT+gfNMTUM1LWMc3kcvFTQvGJEasEX\n12pkrq22VmItQuaqwCQ+cLjdmDFjso4XykEMaKriCIKomBGPH3XUUSmwQEQHDDgmhqgC1VUCVXe3\nLL300rnjqXxgYMSiX+mqf+I7XtRG/p/+9KcpMPm+yiloodINiqn8IaYss8wyGQs7cgiTgNiEHaip\n9hza2ZO8yiqrZPxIt7DRHTJVTcyvNl01n3u999572R7IbI70SRVXtWZc3fqee+6Zde0YF/QzHlBI\nBZh5Mb5i6nnz5qWYaF7oMn4vGw3AOjNP2jZ+/PhkQNCU0AQ9sQb11CoMsaDDDjssr+tZcD8akOcA\n03CoxQknnBARxeGRffv2TVHMnHhW6trs2mr7klqLKsBGjBjRiCjQRzwKBXr37p1oo36aKllV+3h9\nMYVYbtasWYmiPCRZn0c988wzI6J5DbN0B1X6mWeeSRWb6kzFhd4nnnhiyv4nnXRSQxsiIvbdd9+I\nKBC6fOQMdmBnk1RE9RB0MbSjlV599dVU3ankkBrKQ2hjI62izZBzxowZWUcuJqTESwENHTq0SVpj\nyJAhjYgipnaMDyY1Y8aMrKu344di7r52kekzXQCDmjt3bvaNziKeFhtDKMqya9stZZwnTpyYKIgZ\niGGtpcMPPzz7uO+++zYiihSkfmEwbdq0aXYMsPiVrmP9VI88wlA6deqU/2ccIbM1qxZcTA3dITR2\n8dJLL2U/fNfageqDBw/+76emTBDB67jjjouIYuDef//9fNA1CGX24EsDWKA6S9x55513cqul1Af6\nYzFbuB5y9NoAEcS6du2a92dy1ChW2aS0PMyK5y2IefPmJa1yXRNB8HDml7diWODuO2fOnKSUzrwm\nvFgAaD1a7WFCw7Rvp512yvSKB8xDsaj3T0cUWwwdRoAqo7LvvfdeUnZCWPVMbkIUau4anO1yyy2X\nC184Zc7MZfXtDWi4865t4WzXrl2m3VBo5jtlQ/mBCDGr/AYTb8IAZNWNLNa301DRbeHPk08+mdtU\nR4wYERFFygnAeDBtGzX/wg+OcptttskjhoyR8dSuxbWaZtdWWyuxFiFz9e2I6Aia1aVLl0QudIlI\nBVV4GwII74fyrLvuuok20j22IBKZUFxIQChTIKK4YujQoYkACjOgub+jMhFF2gol1F992njjjfM6\naJZ+oIUoHGoO3SDfaqutlvQZsqGaKoGINYo1IJITPgl+PXr0SNSEZNI1vls9HxxSSodBfWxB+iWi\nQBntZe6BXUFhhREDBw7M8S2fqV6+PhHN56SiMJxzzz03IhYimuuiwfrvYMSyuR80ZQTIPn36ZPpU\nCGCuIL2QSBGHN5s4LbZLly5JzVFwqI0RGXco63MYwsEHHxwRC9mBecdmMU3rfnFP56yRubbaWom1\nCJmleXhiMQYv+NZbb2W89ctf/jIiik3pRDLeT8wqDpeEnzx5cnppIpn41DW8NQByMIgMUX/+858n\n8hKKeFRIUTZeVRGEDfPQd9q0aYkkShihtuu5hjZUyyY//fTTZCnEQh7fWChBJBpCJNd2GOHcuXMz\nBeI+rg19qqb9iinMHXZVbrvyRnGoOYUuBCnCHbSfNWtWohkmRNRTqmv+tR/6Q1bHCvfv3z9TUO6L\nGWJJZYPA7oc9su7du2cbHPVEHPXWRYjtYAVtMmYLFixI/cY6UEePJVpnCkKwL7qD52DVVVfNuaIX\nEAkX9S6t/2Q1MtdWWyuxFqWmDj300EZE8f4g3kb8ePHFF6cyx1tX3zDPm0NXMbQ47NVXX01k9m5h\nDABiip0l212Tdxdzr7322undeEJpDbHs6aefnrK/Y5Ek9N3PZy+77LIsapBeok5S48WCtAJxJcTY\ndtttM86FvGJnqAm1IIhrQijq+jvvvJNpPP30f1D+1FNPbZLWOPzwwxsRRdrN2CotHT16dKaroCrW\noS+KLCjntArXeuSRRzIGx66gDwbgs9Vjo6SQrIu77rortRN9LB8LFRHx8MMPZx932223RnkMITTG\nOGfOnGYpP+k8G3roN+bffZVqNhqNZGT6qU12mmE1/i7+xfas0XHjxuXYYAjGxHP14IMP1scG1Vbb\nl8laFDNTankwHotnWWONNTKvymtCMrGcV64o0oeYvPyUKVPygECfcXA6RKb6ya3K2UEXcXKj0cg4\nxzWhIUW8bJgAZRhrETv9+9//zk0gctliJ8gLGXlmCAkhnn/++UR6CCGusuWTQWxoJVfp+7vttlv+\nn7mhmivoqJoySUzJuEOnTp06JRJDVTGkGNU9tUO8Dn3mz5+fOXN7kV3D+qBqYyly1/pIZd9kk02S\nISg0sQWU6ls284y1WauKaCZOnJj5e22SFakq6ba5Yio2p8yfPz8zHnLW2Io16pmQz4fQSnMx2O22\n2y7bqqDEXKrfWFyrkbm22lqJtQiZmfhD0Tx0Wn311ROJqMdQDgJDLL9TG8USI0eOzLjDpgE5O15N\nvAHteENxqvb17ds32QP0xhh40rJpG+SBjDY2zJw5M5VUxfDQVFwHzasvNaOIvv3228kcIIKXm7m2\ndogrsRpsQty/5JJLphIONbEW8WDVoJF2VjcvNBqNrDBzDbG8OLaqf0Byqvvyyy+fCGs9GG/jQhex\nTiAd5VxueYUVVsj7q6qjU5j/smFM1oj7Wjvt27fP9YpFOdbXyTXWpnWIgVD+//nPf+YcYgIYqEwE\nRmh9uKYxs+FlxowZuTbkt9Us0GUW12pkrq22VmItQmZ1ruIhsZJD0L/97W/nUUIqYqjavDpPLE48\n77zzIqLYPLHXXntlfCMGk7NzTUqi3C0vLz/Ks/Xr1y9zz2JCyqsacX2IKLZAyv8qjleRdeutt+b3\n5BN5XkhgY4c4SHUPj7zNNttk3Ch/LZ6qnoNlCxyUU/kk1l511VWzBhg7Uc8uzvs8g+CQhZbRs2fP\nVIKNd/UMMGe/YTn0Asxh+eWXT6THPuSTqb/6oh5ZjA+xIOqYMWMSIc8555yIKJiXMS4bNoHNyJJA\n1z333DOZBdUYK9Q2uWDzI/8sz92xY8dsEwUaO7F2KdGYKdZlXKzLtdZaK/8PKxFnV+sovshqZK6t\ntlZiLUJmtcu8nliSJ7/uuusyRhLXiW/EoWJXSrTPUx333Xff3EYI7XhIJyJCajG1GMjhBZB6zpw5\niQhytbYsOs6mbNgC9mBHl5e7f+9730uGIVYVJ9o9Rd0UfxkbaPLuu+/GkUceGRHFzhr5TEwAmtAT\n9IcSbWfWpEmTsvZXrMbLG4uqYU7Gg3ILMd55552M99R36xtk1nc1BFRf89CjR49kCKr2qq9ahWSu\nrcrPdkdzvtlmmyVDEPfqg+qrsplv2zhPP/30iCjqq+XuIwomhz3IhjBziAlhhP369cs1aG4wPLUX\n2CHGZK7l96n3EyZMSK3HHGKPdg8urtXIXFttrcRahMyORIHQvDsvu99++6Vqx7vj/RBEDSukpuRC\nhkceeSSVTV7Ozio1yWpX7RUVl1NoeeVHH300YyieUTysAq28rxmqigHFquK5oUOHJpPwGRVNYmOx\nYHWvtc898MADzQ4z1H5jRhl1LYjn88Zn6tSpOX6uAW0c1KC/TH4TmroWVGrbtm3OobjO3FG+tc9Y\nuAbE7tOnT7IKiKwvVGrX1g7xq1hePv/dd9/NWBXKUe4xB3nZiGI9QXqISbPo0aNH/hsLkBOW+cA8\nIaW2u++MGTOy9sHapzxT3o2J+Fec7kBLmsZtt92Wz4T2WDtYBlbxRdaih9nDotMeNoH7Cy+8kA8S\ncYoDsJHCgkU7LRCD/qc//SmprJ9olYkilkmyK+qQdlHscMoppyQNQpFQRZ8tG+HJYjXI2vzmm2/m\nJKBCJh5dJRIScKonZ9x22225EDxYClkIL9qqfFD/OEYpmffffz/TV9XD5st0smwWCueC4nu4pk+f\nnqmxUaNGRUSRdjOHQij94FxPO+207IdDEDyAHKLxM/7Tpk2LiMLpuZYQq2vXrjke1ZNPqpsoIopx\nd9IN4cs62GqrrbJ/xDehElotRDA/nKnPnXLKKTmO1hoxEDjoFxBR8CLtJ/yYM2dOOuLymzgjinWw\nuFbT7NpqayXWImQmrvBK1WNjttlmm0wX8NooDbqLdvFQEByVGj58eLPNCQQxpYc8GCpz3XXXRURB\nu227XGGFFZq9YgWd045FGW9u8zsqdeCBByaiSGMQKVA+SEmscYwSIfC8887LkEJag5BHULSRhfBS\n3eZovPfZZ58cRyEBtuRIp6rdeuutEVGk6owlWjpo0KBkF1JoEMv8Qwwb7I0tqnnJJZckdXUEElZl\nPBTdYBTVIhNhS79+/RLtFG1AVmFe2SCw69mWaZ4+/PDDTAViXoQ0LMq4S9dBXyzsuOOOS/aG2fhd\nOa1nA3tAr8tp04iFzKO6UUUYtqjTR/+T1chcW22txFqEzGIlsSwvyjsNHDgwPTwvyqsSr8QyCiQU\nLTjFctKkSSmKiKPEo9UXfPFcJ510UkQUHlXsucoqq6QgASkvv/zyiCji7bL5rHgPupVfCiclQagR\nx4mN6Ani7x/96EcRURSA9O/fP+Mr6Kh/hByfheAOg/B3SPHOO+/kuEFLcV712BxG91DcAqXoAtOn\nT8+Uk5hdDEn4xJx814YAY9GpU6dEcQwN6/A7AdS6ULKLOYk5d9hhhxQrFfVINy2qj2JzzACbsUX1\n5ZdfTvaIxWBgNlIwDMjhfRjf+PHjc7wIjA46sHYwQm2ne1QLUNq2bZvX9exIjS7q8IX/ZDUy11Zb\nK7EWITP+L/0Bnairv//97zO+UsSu1FP8BU15dfE3T9W7d+9EXiVxPCOFVvwlFQIFeHWx29SpUxPN\nfab8HqqqQavqIW1QdplllsnrUeMpq8ZEeSoPrX/i4ueeey61AHGVrZe24Pl/8Z+YXYwHtf7973/n\nUa+2BWI11OCqSfM5AkppLnS97LLLUrVV5ghdsCnv7frxj3+c7Ygotqy+++67GV9SZhWLQFOxuoIN\nfRVLWg9PPvlklkial+pRTWWjllOgpYSg3m233ZZxOm1ENgEjwb6qaVOM76OPPsp5pb5jh64t/sZe\nxcz6Yt188MEHOYcKSTwjPru4ViNzbbW1EmsRMkMG6iWvyyOPGDEiVV3ILHbhRXk/CMEr8qTLLrts\nIjLlTzziyFFICf3kC3llOb2dd945Pbz2+Ok90WWjOENx8SW1cfXVV082wGvL64orbaeDTFCtrCFg\nB3K7ijSo2+JvaAlVjJ3xmDNnTqKnXLC2ft67fd2DHqGowYaALbbYIpEPQ7DdT8wOkRWxQC7z8tWv\nfjXLZSnz2kN3EcPKQxsvrAo7Gzx4cH7XZ60VqF42/1c9JEC/11lnnWSP9AYZF4o0ldwY0QrEtoMH\nD86tltaXrAK26qdrYoLmh+o9cODA/Kwcud+h++Jajcy11dZKrEXITMHjycQDtgMut9xy6fWouvKa\nYrPq8T3iArFHz5490ztDJOV0fkIy+eVq5Q403GSTTdIjOqSPiu3aFOWIAnnEd1WluFevXnHYYYdF\nRIEK4lcb51VWUSLlOeVuO3XqlAyC1iBnbcx4ZMxHcT7WA9HfeuutRCKojdVQU6tGB6Dcis/oIVOm\nTEn1HDPCVMydmBLqiWX9nDBhQo6h8bCdFcpXSzJpEVhWmR1AfoyQqSsoW7XSDyKLZTfddNNU48W5\nNvnI76po9HoiinW5mszBHJRxCFw9sIFSjr1am9bPY489lvPuPjb41McG1Vbbl9RadNTus88+24go\nPJm4RGzVoUOH5P0qfeROeXdqJfWX2k2FfeaZZ7LiCwJQS1UTQUOHskN3heoUzCFDhqQyy3PK6ULs\nc845J8/XOf744xsRRQ6Uus1effXVrBxzUJ3tiGJp/ajGeTbdT5w4MVFLv3jpH/7wh03a79pYDYTy\nvSFDhjSryYYEKqB+97vfNTk/6IYbbmhEFIjlmnLKSy21VMbfmM6BBx4YEQXyYk7upe6gjIZYlLnC\nGBww4P7yz65B5RbL77LLLs0OlJC1EMvef//92cfrrruuUb4fpPZ7165dc9ulugIM033EzHLW2JWx\nevHFF5PhULXNt6wF5ll9gaL+0UW6deuW84kx6B9mdtFFF9VH7dZW25fJWhQzU4+pvhRIcef777+f\nyMSbq6KBjDyW+IMya2tcWb2EUJRC31WRdfzxx0dE4UkpqPK2U6dOzZiG0qqee1G12Tyi+JNSSVnd\ndttt8zpe4mankLhWTCSuL7+zOGJhpRMFWvvF/JAHikBqjIM2IRMwbty4RGQoUt0+WTXXrr4TWhz+\n8ccfZ9ZC7bVdao5Iqh5XbExpDJ9++mnG3baVWiPVI37Fp+JF60DtdvmwBH8ztovqo1gcE9QH9dxt\n2rTJNWqdWIMQGKvEWmUuvIK3a9euWdHl4Ar9wBaqeg+GRsWG2B07dmz2Dmlrs/rCvi+yGplrq62V\nWIti5lNOOaURUXgM+Vyx7L///e+MDal98oniWp5ZzGSvMmXx3nvvTWW4vPspoohHKbG8PXTy4i3o\n2L1791QGoSvV1M+BAwdmPLLJJps0IgoEojJSUadOnZqoBB2pl2I+sSfkMVZQ5fbbb896dTGSmFiM\npLqMt1dXDiEcb3TkkUfmjirsBROgSRx44IFN4q1tt922EVEcK2QMxfxPPvlktlltuvjQ+Pv/6t8h\n9cSJEzO+hHbYjuOAxIyqyuSfxa8Y3Y477phohqGYU3Xe+++/f/Zx6NChjfL9rG9K9c0335xr0Ljb\nc489qdaCrvQRY/bQQw9lhR0WYz3IiGAPFH/rHAOiM22//fap6DsWyjpwv/Ia/U9WI3NttbUSa1HM\nXK0ycqwKRPzss88yN2m3iryh+Jr6BxkhCXT/5je/mUhE0YTMdgRR0yEBFKKm2g3TtWvXrH+mzNql\nAyEgakSBfJDd9aDqMsssk/eS360eQ0uZFPeIjewWGzJkSHp8aqr4VQ5WvCeeVflWfS3omDFjck6g\nJZUeUldNf8X+WIB88EEHHZS7n5yGIQ+uig16Yl3+366mvn375jqAghCyepyO313beOrjww8/nJ9R\ndQXdIHTZIOSll14aEcVeeFmTYcOGpYIunrWTyXVpQubaGGN3W221VcbxWIPY3Jqk/B9xxBERUax/\n/TNmEyZMyH9jI+bds1Neo//JWvQwuzhq6Zwm6Yc77rgjE/kedGcsE0eUUaLQhAGUokuXLrkpvPrW\nCakamwSc8GnjuXah3QMHDszFhO546Cy2snlYLDQPJCo6YsSInCxOSEkjakSAsmBsZyOmrbXWWs2O\nvzEG0jbSZwRHi8y1iV3f/e53s80crHa5R9VQe3Nmc4cFPH78+HS0HBHnYsyk+1BFi8/c9+nTJxe5\ncefA0E2LX2GGsfbAckpbbrlljq2HS6FLueCHKSQy3gQpxT533nlnbkoheJqHqvO2ZrUFzd9uu+3y\nlFdggSoDGkVKnhFip/BS2z/66KMcPwBhHS/qWKT/ZDXNrq22VmItQmZeiGeGYGjXdtttlwKYUjSC\nEe9qm5cUgpJG3zvqqKPSM0EgAgukhsS8mzQX5CJsPPXUU3lfbVdMAVHLhppCfBsKpMK23XbbpOs8\nMW8OedyPoFMuvYxYuBldmgQV813CmC1x6JXwQnGJ/r377ruJLuj9L37xiyZjUjWinlQaAc1Gi8GD\nB2c5aTlcKfdJigxFJy6VQymIj5qi5CirMAcNdq/qZpopU6Ykc0FDiUtKRL3VMaJgGNBX+a50U6dO\nneKCCy5o0iaIbywJf9ah8MeYTpo0KedC2Iil+Ix7YCCEMtTeuI8fPz7PURfWWFPV8tUvshqZa6ut\nlViLUlOXX355I6JAMN5XLPXaa69l7MbzSNHw/OJZMRs0EmMvv/zyKRbxZpASuvG+YhjihvZIMbRp\n0ya/o7AEKmIIL774Ysr+l156aSOiiLN4fAxhzTXXTAFNTMbzK/3k7QlK7ud9VQMHDmx2PjZkFo/z\n1IQZ9yA0ihmXXnrpFOvKMXlEsXFl9OjRTdIaV1xxRSOiEALd0zitv/76GcNJs0lbKYOsnvtdfXfW\nggULUtxTvouBQWCpKT9/85vfRETBSsrnklePA3ZffSiXc55xxhmNiCL2ptk42GKttdbKtYCliVUV\nuoiR/VTMoU/bb799rm9rznNkLqE8jQKboQ1hF5MmTUqW5zki/tnY0mg06tRUbbV9maxFMbOYSKqA\nYikd8Oqrr+bWO6hTPRRPuZ5N60wSvm3btom83ldL+RZDiqFdEyopVOCx77777lRYeUrtoy6WzfcV\nyzvKRgHCFVdckTGReIpnNhb6gXHQApRmjh07NmNPsT/9wEF9EFmZ4c9+9rOIKLQJJao333xzFpa4\nL1VYbFw1rABiKogQF99yyy2JXD5jDCmxNlj4nPGGTu3bt8/YF1MQ7yoiMV4YjPGxxjC3+fPn5/ZB\nf/PTuiubNlCRZTMcp3vttddmGgyDM4eKkbTN4QQ0CvPTtWvX7Ad2CLXdxyEV+qcQChOROnv00UeT\nEWAc1qgy2sW1Gplrq62VWIti5tpqq+1/r9XIXFttrcTqh7m22lqJtUgA23zzzRsRhVAgcCcczZw5\nM8UoZXtK0qSziBeEGIINceFvf/tbilNEBLtzpKoUHriW9I+CDhL/hhtumMUH9qLaaWO3zrnnnpuy\n/6mnntqIKFIW+qXO/PXXX2+2l9u9FVpITSgrJHwQBC+77LIUBRXdENqkbxQxGBOiG5HLzpzll18+\n56Jakqig5sgjj2yS1nCaCrFFYYJzyUaNGpXiJNGqeiomIc5ebmNqZ9zJJ5+caRXFFeZBuoeoqB1K\nRxlRcMCAAVlcYz789JnyHJ5++umNiCL1o83lt7CYT2vQuKpvJ/jZd37MMcdERLFHYPr06dlXYqTi\nEeIaUVBpqLVrzz3R7Tvf+U6mQBXyWN9C4KOPPnqxUlMtepjVGVsocneqqx599NHsjHyrul7foQKa\nPJNKubvgggtyk75B5gjkqCmEHhALRQ7TYLRp0yaVYXk+SjJFvGw2WlAobRwoH4JHQadmy8FSdi18\nC4ZiKt/+ox/9KNVgD68xc18L3hhakKq8OJAuXbrkQYHquo03Z1M1ztYGgJ///OcRUTiBjTfeOMdP\nLT5nY0MAZ8kRq+Wmul977bWZO+WIOFrzz2FxqmrJza38d9euXbPfVdV3Ua9vcX1z6WgpbZ4+fXo+\neP6mjl52wQYO96PMu9aBBx4YI0eObHINv8tAmHcVX8ZZNZ+/W9MRxZwY97oCrLbavqT2/5Rn5rl4\nSDRhwIABiS6oih1A8p48EpqiaggdmTdvXh4hg8Z5UZhdUzZxqzZTsSSXjD5tscUWSWtUEVUPYisb\neq3iC9pCv7XWWiuRDd1Wew6dIJAx0RYUbfbs2YkatnryyBBCzld+U/WYaiYVaoMHD84cLMYA2aBZ\n1TATG/DNi51q/fr1y2uYE2gPTdHRvfbaKyKKXDoEe+ONN5L+q+SSE3YIBfQ35uYQW0HxP/zww6ya\nwhCsu0XtfMNmjBFz5PNf//rXbH/1dUBy4tY5aq7eHbv8+OOPc84ci6SOHyNRtw5dtRUt9wy1adMm\nry9XbUw+7+inz7MamWurrZVYi5DZXk0CBAR17Mro0aMzVhBLqoQi5qhuUQsMWXj/du3apXhhDyrP\ndfTRR0dEUe+qQsdrU9X3iv/uvvvuRFI/GS9YNnXO0Iso5MV1t99+ezIP8aKYX222ml0IrZ4Zi4go\n0BC68+aqlsTzxrn6Cl210GPHjs394doOCSBc1YytuNy1sYXXX389+w9diXvaR0tQu41BqZz75je/\nmW2s1uqbI+IljcEuI2yAHtK+ffsU/LCc6qtvy2YnVXV9ifdHjhyZe6zpKJgQdoCZYW8XXnhhRBTH\nNT377LPJfLAVa9IYmENojxGqu8c81l133awKUx3pKGZztbhWI3NttbUSa1EF2IknntiIKFIqPIhr\n/Otf/8pUVPUgPV5e6oanctA9z7nmmmtmzKYmWzxSfRWqOFGs7B4Q7dhjj83aZR6Uksyrd+3aNWX/\n/fffvxFRKI4MIgwYMCC9OgSAONpvRxGElFbhoZ955pn8rP2rdslAbIosJKZ48v7Yz8033xxHHXVU\nk3H0EwL07du3SVrjmmuuaUQUMbP9tu7VaDRSK7j++usjokizUNWlbMSeEMw1lltuuYxdoYv43/jb\nIwVo57YAACAASURBVFyNnaWysKtZs2YlckF5LA9T6N27d7NdU+eff35EFOqytk2bNi3ZCAVdW6uv\nFKJh0D8w0dmzZ6dWUo31ZWn0z/52n1P3bQfYzTffnAxQn60ZKL/TTjv991NTBnNR28r8boItdnQJ\n7UIppZs8ZOjqCiuskAPi4eUQ0D8DaRAMlK2BaNiZZ56ZCwG9r56v5CTOiOZv4dM2xfoPPPBAOgyp\nKZsRPKDOMvNQczy25HXt2jVTbhwbuipNQ+ghsvgdJdX2/fbbL52GxUo04eiIPEz6zpnR6DnRZ4kl\nlkgKrH3SbMIpY0bUci/j9dFHH2VqCd003x58AhVgsIA9aASrfv36ZcropptuiojCWXsYy5tmXB8A\nuA8H0Llz5wwLrA3rxQNI0KuePea+48aNy1oBTlN/rUnnqgsVzY9trLZ67rTTTs0edO0AUotrNc2u\nrbZWYi2i2SeffHIjokiz2ACP/kUUHhCKEyJQGUKLY1xUvfDEPXr0yKIIaMG7+zu6wzO7P5R070aj\nkZVovLBKHGLD5MmTs/FXXnllI6IQ7VRxobXlNkBeDAQyO2kTRVM95Fp77rlnfhYFq74jC+IZX0zE\ntSBhmzZtMiTBFCCd+7/66qtNKNrNN9/ciCgove+5R+/evRPd0GvIAaEhiLWDll9++eURsRCNzIX7\n+A7BDvoTglBM9za+a6+9dopN1SpC7Ro+fHj28dBDD21EFKGAgiIhQr9+/ZKdKNZxfWtDBRzEh5SY\n6IIFC1IUFQqaQ2Nkvd91110RUcyt47Ss6b333jtDEeuW4CgkufPOO+vDCWqr7ctkLYqZHZ/Ce4ph\nBf+9e/dOpBo+fHhEFAl+SMxDOciNRyYsrbDCCilAiEN4Ysfn8PaQGdJ5Z5P464033kjkcT9eUCFC\n2XhqpZe+qx3LLrtsxq8OjCOAEdSghTjPd8Xa7733XiKeGFRaDvJoPzELyhGJoG+HDh0yPSde9X+E\npapJL2JI5sv4L7300nlN8bgUjpiV8ASZiZ0KhT755JPUOayNY489NiKK92lhMPpKEJXyoyssueSS\nKWYZcyxL+tNaiyjQVbrJ/bGrpZZaKuNoaSv/J+WmSEkhkLSjwxnWX3/91BqUfGIeiqCUPvsde6Qd\nld/F7BmgG/nsoo4S/k9WI3NttbUSaxEyK4Cg9lLueMoXX3wxyzR5P0q3GEYqxCF85eR5xMKYVDwL\naaUrqM1SR5RP6FLeEBGxMP4WH/GQYkxKbdkgpjQKry41dO+99ybSuh4UE+MpNXUt9/PurUcffTQR\nTbupllCFJiHNh4lQvRWbjB07NhV8LAKau0bV9Nu4UH0dRv/ZZ58lA8AYzLOSRO03L1BWrP/UU08l\n2mAoGI2x9JZQG2FsyKC+Y3SPP/54qs80BH2jLpcN8zJPxlYM+9xzz2U/6Cnm0GcgovVWLg82Dg7I\nN+4yEWJzDEkKUBqSTiJOnzJlSjJLbAbzdd/FtRqZa6utlViLkJkXEo84DE4ueYUVVshiex6Yd6f6\n8YbynJRCcdno0aOzbI5iKIbgGaFRdZsfdClvVBDP2UigMJ4CWzYIpF+uD6Hbt2+fBQQ8LlWSR4a2\nvLvSwHLRPGYhJw0lxZXV93FhKmJ6yLTzzjsnCxGvGmfIWDXvFRarKpGVL7377ruzGIh2Ic9KZYWI\ncuh+2n++xRZbZPmsPkJvDEbWQ3yqZNLnaRprrbVWxqpyt+ZQHrhsFGgxKTbpdTFXXnllsgJZAczS\nOnM/TEDxBrRdcsklc50rQzUPmIa8sthaQYo6C6i7xx57JDLTMRw7jSksrtXIXFttrcRahMwQoVoi\np+pr6tSpGUeJlcRwcrc8M+8jhoN+/fr1S49ku5xtY9RLcZCKKDEeJBE7b7TRRolUThqxNa2cG2fi\nGrlksZWYdfLkyRkLV0sCaQOQWhUR1MIqZs+enZ5YTGxssBa5UaWaVFe5eOr+5ptvnjGYqjBjQ4uo\nGgYEuSnTNobMmzcvrw+BZSLEkMYXgjFoOH/+/EReMbCSVflsc6kiik5h7MtvmjQvkNF8L2oLpLyu\nqi6ahWxD9+7dU72WJVAD4Hdr2FqR79XWjh07Nqs001/MB2uwfRWTs23U2K2xxhq5zr3sQTbFGCyu\n1chcW22txFqEzOIbiAgJIcz8+fMzNvDaVSgrRwjBqJViKV5wiy22SPQTg1EKHTDOc4l55Ph4ajF8\n586dM1YV/4ptqjXL5fvwxK7Hq954442ZV5ZzpYRCFGq2OJfOoI2bbbZZjomKH/0RM2mrmM3nIQrN\n4IknnkiUh6K0Cnn1qkHg6pFFctxHHHFEs9elYA76Lk7EHORHxYF9+vTJsRRv6yOmQlugc5h/+XEo\n2blz52Q74nv570Udq6M/YnbrSyXi4YcfnmvAWPksNK3m6GVa6C577bVX/s11qzl4DOHss89u8jlM\nVBteeumlHBM5aGOxKF3nP1mNzLXV1kqsRchMhaXcis/EI23bts24ppqj5e3thHKiI4/GU3fv3j29\nmHhHDAllxWa8m6oy2x3F9EsuuWTGHVAcaqtEKlcPyfP5jkPY1Or+5Cc/SRUTWoqnoan6ZGMlZi9X\nIFGS/U0MKjeKNYjLHb0kDw3tevTo0YzZVOuqq0a55fXlrqH9GWeckfXFELF6tA/lWWUUVMcO3n77\n7RwXsaG1AuVtARRLYy40FYcY7LbbbrkO1EZbK+qcy4bxqXMQ55e1hfKL1yMKFoAJGV/9xGbEu88+\n+2wiLK1CNaT2y8XTk/Sfuk5Tef3113N83V8fjNXiWo3MtdXWSqxFu6ZOOeWURkQRO4kXIWP37t3T\nWzt6lKoNoe0ugbKuAX26du3abIcTdRGSQWAeFNqLObCDhx9+OCvSqKg+49icW2+9NWXtX/3qV42I\noi7YHmhe+P3338+qNLno6kvTxI/UWRqCMZsxY0aipzhbzKSqzD1kApjPYxURxd5iXp1+Qc0+77zz\nmsj2p512WiOiqOIT21KM+/fvn/3VN3G/DIT2mUuI7YDCddZZJ/8mV069dl9jrO9QF5IZv5kzZ2Yb\n/R/lWPvOPvvsZjvf3B8jwzxmzpyZiO771df+Qkb11dhVOd7HLMprI6JYk9iNObP+rQ9r+Yknnsjq\nN+NpDwRmdOWVV/73DycwMSaVEGZiJkyYkHTGQtQg4pUFS0DwkHkr3tprr53FEyZk1KhREVGcDe3B\nkMpRoCHd5AHaeOONcyGive6vyKJsBBA0nZiFmrdp0yYfWn8zWdIWCl2IKuiXyXvzzTdzodoc4UQP\nFI1zUrapPwQm195oo41S8LHAzQWHWDUUXkrNAiqfHqLoRgmmhalvaKdwRypLMcaVV16ZqS+Cp75Y\nMx5MdNM9FNA4o23VVVdN58ypV9+bXDYPmXERfgCP2bNnZxjlneHm3fZMbfKQAQR0/6677srwxHu+\nUXfXlE4l4qLM5cKTiIUiozYq8fTsWCeLazXNrq22VmItotmjRo1qRBQliiR8Xrht27bpvaAI8YhQ\nwEO6BkpDWOrcuXOmbAgUTmyUIkLlIRmUQXGIDWussUZSKEcdKS/lWR966KGkMN/5zncaEQUVgnau\nscceezQprogoSgwJfJgJOgkFfH7jjTdOZDEGkBCzIB6ibjw2ysi7r7zyyinwGEdiob/vueeeTSja\nyJEjm7yCp7p5Ys0110xERitdi6hUFQr1QxnoNttsk+1RzgiJfBaSQWBj4t6o8N///vcUBrEggptx\nOf7447OPl156aSOiQG0ITeTq3bt3rhvhClZArMN8jLNwy/h37do1C3n0x/3KW0kjCtQXdnpW3GPL\nLbdMARnDJB76zNChQ+vDCWqr7ctkLYqZCQHSMDyzzRJXX311xkaEAcnz6gvEFDuIXf199uzZeeSN\nOM41pDHE4bahEdkgKi85b968jDelmaDMouIRRQhQQkwrdfTUU081E2iwAkhXPWCPqKIPO+64Y75l\nQ7shAsRwCANm4GglqThx7oknnphFCVI5jhbCIGy9ZOZQ2aFYHhv49NNPM/4Xu0tFao94nGaBKZWO\nYmry7qrytaB99YVrRE2/YwrLLLNMfpbOgrlBzrJBSjGqdBlBsF+/fnHttddGRJEOg7jVtrqWdWgt\n7bjjjqnxmBsHKNB7MBEM0HhbW4pl5s+fn2vIOjAWnonFtRqZa6utlViLkFnMwlOJYaWXnnzyyZTz\neSTqpVJF2xvFHLyRuOjWW29tVpwCBcUh4iAITaHm1cWn06dPT6TiScWI2lM2yivviU1AqmuvvTa/\nB6Epjz5j6x70ZRjB888/nwc0QACqMPVeDO3++l3eQBKxMA7THqkfaUJv+aiarYDG1jWpyKNGjUq2\nBK2xChkJ2xShkBQi5vTss88mWtMbjA+2AxX1Far7f8xu9uzZuWZsWlB4YZ7LholIBVl/0lCjR4+O\nE044ISIKFuPwA2xGdsEcu4/ttJ988knqRebGK2wZ3caaxDYxV4xh7ty5udGDrmR905EW12pkrq22\nVmItQmbeBKJQ3cQ0e+65Z+bdxDc2LThIzqEE4lpoTw0+6KCDsoD/Bz/4QUQUucIqQvH+EBpjkA/d\nbLPNMjZXLCJGtNG+7P14TSoylIOQjUaj2dHBxgQyKn6BnjacaFuvXr3yyCRsBCKI0eTz5TnlcW2R\n0+bBgwcn8ogReXVKrc0xTMwMdRWLKDHt2LFjZgWqKjIGpG9YlVjaeA0bNiznU+yLCVB7zaH2U3T1\nQwzar1+/ZHnUXcwJqpfN/NAu1AOY0x133DHfs4xVaSME9p5psSuWpVR35513znGkvjsyicJOPRdn\nYxOKeq655pqIWFiSS3NyoCBNAPNdVE3EoqxG5tpqayXWImQWB/Cq1U0Gu+yyS8YO1eNLeUrXEB+K\nU224+PDDDzOmtJEeIkFmOWxqqvJCcbF2jRs3LlXV6uFsizpyRv6yemCcUsNDDjkkUchnVAuJeyGB\n+IqKeeqpp0bEwi2GGEA15vvhD38YEQs3dEQUcSymItYTf86fPz/zl5RwjEc7qiZnCjkglu2s7dq1\nSzYDZaoIbSzF0piRa+t7RIGiFHBoaD3IXUNoiFx+a6aYvKoP0GrKZg6tUSxSBuDBBx/MI46VeNIA\nxNvidijqc9jLMssskyq2tplL6xqb8m5vxxnJOpQ3ujgGCfOovh96ca1G5tpqayXWogqwYcOGNSKK\n+l5bxORLu3Tpkt5M/bR4ACKqnZXboy5DhtGjRzd7XYh8ojjDJnGbC+T0KJa88Morr5xxlf+TD1YT\nPmPGjKyuuffeexsRRdwpJoQiM2fOzDhdbIyJVLccQnWemUL/5JNPZq7V2FNyxa/iXXGksYGivHr3\n7t1TC4B44izj/Yc//KFJ9dC1117biCgqxhhUbTQaGZN7L7YKPGzLeIuRbcOkC/z5z3/OQ/CwJ5V/\n1de6QDt6AdYBsffff/8cJ9V1NBSs66KLLso+jhkzphFRrA2m7W+88UYeXkhFdkijajVMzzUo1/o3\nYsSIZJSYANaCidmmqX+0IvMEyW+66aZU1c0ZzQLj+eUvf1lXgNVW25fJWoTM++23XxOv7tA0cck6\n66yT/8f7iXe9xkPNMvTxakzx8Ve/+tX0gJRg8Z2aYF4QStoiBwXEml27dk00V5ut2oZifMIJJzTb\nAskTi/PELk8//XTG474v18rzuh8kVlUEze64447cnQMZeHleXI2zHKX4F3o5mubNN99ML44ZVF9x\nsttuuzXx6kceeWQTdgX1KeoDBgzIuFsM6fWj5d1jEUUeViyvcu2jjz7KTES1jxiZCjljbDzFmhjc\n66+/nuOiAg6bU8u80UYbZR8vv/zyRkTBqhyfJM7u2bNnzqH1Axm9QlemQz/tLzBGDz/8cM6v45Ao\n7uJxzE8cTNPAOLCsddZZJ9d+9eUL1vGQIUNqZK6tti+TtUjNxvPtW+VVxTmvvPJK5t14FXE15ODN\nITQ1VnXRb3/728zN8dLURTtpxB1+OkYXQlOfjz766IyfqztfFnUki7gKA4AO4v9//etfeW19d/yt\n74gvxTvVw/pWWmml9NpUY0aBVbcrz4lx8NyQ8Nvf/naih91HkAgTqJoqI0fEiu2p9OPHj8+D3OXS\n7eum1Moh0xKowRjThAkTclyo/jIRUBHKmjP10n6Xiz/jjDOS+VkH1hLVvFxnDz2hLkYAOZ944okc\nZ6xEpoEWQbPBHrBH6vnjjz+eY0PPwUDF8e6HKdFFrEN5Z+smIpodcVx+lfDiWI3MtdXWSqxFMfNP\nf/rTRkQR7/LmPOPbb7+dsYA410kbkFA1FS9ePdzugw8+yCqh6kF9vJ6YRtWNGA8KyAtec801zdCc\npxaPXnDBBRmP/OIXv2iy11eOFLrvtNNOuVPLvmg5cblBCjwvD2Gg/PPPP5+oqXJOHlmsZHy9LgeK\nGVv28ssvZyxmnMWRKq4OPfTQJvHW+eef34gokMM1MaP27dtnXbP7Ulkp0tRrVX5qB1SIde/ePdcG\nVkFDkSmgHPs79LUu6AMzZ87M+xgv6I2N3HjjjdnH4cOHNyKKtQLFraGOHTtmG8yDGgEn6GAc2ASE\nFod/5StfyayN+aUfYZzyyarJtMO46P/kyZNzrdgl5VmgWey9997//WODPKCoI5NAHzlyZIozGmSR\nG0ADZ2DKZzNFLBQbiBXVtzx6gNBABfJEJqWjChB69eqV90d3UKjq2xgiigfcApfWUlZ5/fXXJwWS\neuEkUGbhhaOHhCDSKYMGDcr0kYMN9A/9NkYequqbQ6RDIgpKxlnY6qe/VUP/WVVc7NSpU4pj3mRR\nPcfqzDPPjIiCshtL4dEaa6yRzsKCVGYp3WOdnHzyyRFR0GJHRPl9yy23TFG1+r5uomrZhB0eZqWQ\nBLaxY8dmf4RcwgbrTSgAaFBpY9y3b998iB0phLqfd955EVGk4IQbrmkMpRR33333HD/Cq3k2J4t6\nl/iirKbZtdXWSqxFyAw5bHNEdxWgP/3005ngR1UhBDRRukZA4jkh2ptvvpn/5/oQE0UmAKHQhBki\nk8+NGjWqWUoEeqPDZXPipjc22C6IAn7lK19JaidNo3+EMeZ+UmLGY6WVVsrvEhRRZONK2EHZIIbi\nBgLZtGnTsuzRyZjQC6pgBkwpplBGf/z85JNPMn2nb4pXUFWUEk1FE6FNr169knpDd4Uy0M1Y65M5\nhHT6PGnSpER5ApjikUWJfCi40IUAC80nTpyYtN24G2djRvC0DVMoZdtmt27dsh/GDZsiDmONkBra\nSrsKCZ966qlcD1gqYa56OusXWY3MtdXWSqxFAthWW23ViGj+FkaeuXfv3hlfKsLnEcWqiiugjxgO\nGnfo0CFjGMhAcKlu8yPQKJlUVsqzbrXVVuk5ITTPKKZ99tlnU1y4+uqrGxEFAlRLTjfeeOOMb3nz\napoJeknRGQ/sYsqUKVm2Ke7WdzEnhmETh/440EF6Y8kll0xxShyI4SjFnDZtWhPx5LzzzmtEFEIk\nAQ1SYgfl9ihMqYo85hYiQ8E+ffo0OxrJwQWEILE65BY3+h42MG/evEQ1+gf2YWNKo9HIPh5xxBGN\niGKTBN0DMxowYECm2hwYQIvB9BR2KPiA9j6/5ZZbJnuzYUeqz4YhY2POtBUT9cy8+OKLqadAaG3G\n9p577rm6aKS22r5M1iJk3mWXXRoRRYqCJ4FG119/faYUKI1QvLzBP6IoSIAk0Om9997LhLpYCaqJ\nJXg9yievKB0jpnrppZdSmYW2UgPSTuUi/XPOOacRUcST4hoI9Ze//CWVcwjvs7x7VYHWfzHg3Xff\nnchKNRf38trGSAwnPqNcYz3z5s3LVJT4SuwJcQcPHtzEqytZ1W7jL/12yy23ZCypAEbaSkEG1iF1\nIzWJcfTp06dZegXL0VdziBHY3EHLsHV2zJgxuX3QvIqrofy+++6bfTz11FMb5TZLjRm7l19+Ofsn\ndrY2rEEpqupbIV1jqaWWynidim3O9A+zEHdjmeXDIcvXjih0D5uTMN9qevHzrEbm2mprJdYiZK6t\nttr+91qNzLXV1kqsfphrq62VWIuKRtZaa60mrwP1viApg0ajkWKCcjoCFPm9usuHeCbl06VLlzwj\nS9pFTa6XXRPGlOhJe1XPBjvppJPyRAviiWsrBCmnpnbaaacmMQcBrHweFRGOOEWwEa5I4xDtpG0I\nTH/+859jv/32a9Km6hlTBEbpFWPJCGfLL7981qVXzykn8pT7FxHxjW98oxFRpPsURPh97NixOUf6\nrw+EIb9LmWmnVM6dd96Z+3oJc2qRpZWc5mEd2MMtZVi+pv5LXxGilFnef//92UfpU4KrNJRU0N//\n/vf8vj5rk5QQccvrcp0eosjnlVdeSbHS+EtfEUKtTUKrdUcgVaK68sorZwqS4CZt5+8PPvjgf782\n28HqVGy1o+WN13KyOiEnLHdsIVjsFEQPwfbbb5/Hw1oQVFJVRNRThekeJAqqhfHGG2/koNlqabAX\ntQVSLpoCqQJNVc+TTz6ZKqxKKovV4qFyc07UXIv0W9/6VtZmcwQeahkAarf/V/FF+aRYb7XVVs0O\nbue8Pq96yKKyYOROKahbbLFFqrxUc8qs8bf4PWRyqdpw2GGH5XhzFhyih9TYGnNVhA57MH7Tpk3L\nh0hulyM2T2Uz90DEGqEi9+7dO52VfDJFXy7aXHpgOR4bYM4+++w8PFKtg/XNeZhDDsJBG8COut2u\nXbsEI/Xqnit1CItrNc2urbZWYi1Ssy+88MImFIZn4/WmTJmSHph3ryKWqha0hNeVlz3ggAOSVvN+\nNtxDNy9LQ+/lPeVj9WmJJZbIaiq7XFAZucptt902KczFF1/cKPcLnUVhe/Tokeivskml1dFHHx0R\nBZo5GggzgIhjx47Nemn9gchezG3rI8osFwshsIuuXbtm/1BQzME1hg8f3oSinXbaaY2IAo3Mj11N\n/fr1S5RxbVVajtfBFDAyLEwoNWzYsAx5UHOIpH3uC0mrx+diFm3bts2xFt7J+0P38qGFI0aMaEQU\nOXDjb91tv/32WXWIRVpHGI8wDUNU5Yeq//Of/0yGgbWYX2Ol8s8YYTHWOfQdMmRIjo1xRMWN0cUX\nX1znmWur7ctkLYqZxXrVPb2qnB544IH0njba80hiYt6wejwrNB45cmSimnjTHl0xC6/N+6ku8j2I\nt/LKKydaiH+gN88I7SKKw/6Y+xO9ynXC1aOEeW+ikWo0yGOT+jrrrJPMQczn0DuvnRXTqdKyB1j9\nNRSdP39+Io9r0QJU4g0fPrxJn9SxGw/tJ15NnTo1WRN0syPIzjdjCFHsfFJ19Ze//CXruM0F9uZ4\nHWvIumBETmxr7ty5iZyQC0Jif2WDjJiHdWh/9IwZM1LH8X+Yjrr06osMqi+Oa9euXa4bBxmYI7Gw\n/omDzbG1RDt67733UvjEOLQDW1lcq5G5ttpaibUoZj7mmGOaxFvQgDLdq1evRA+xhJQMpOB1HC/K\n6/KSq622WsaqUjbQUKwJ3Xl17RDrQpabbropd2mJ4SAyT7niiitmPHLggQc2IgoFEgJJVcyePTvv\nzZtiHpRQY6HNPkfxXXrppTNuNPbGQNzFIBG244QXqHDfffelmgpFqdti+b322qtJvKW+3jWkwYz1\nG2+8kRkGqE9tdYwT3QHKYGZQ6bXXXsu20yocigcVq2k4n1c7j6ktu+yyOZ+OJaJb6OOgQYOyj462\nKu+Simi604ySrw3WhPXjKCPptOqRP0sttVTGwo6R8rvdc2Jjarrftb38EgJ/k2rDyKD6Djvs8N9P\nTcmp2c4lVVA+AMDC86AZTKkCD7nOWPzo4fTp0/MhQqtRGYuKmGHTgwG0IN170KBBmUaxiKqCmEUW\nUdBGn6mmbe6///4U+FzXBGi/Y2IYB6SfHTp0SAomj2jyOCWLjOPgII1D+bAEWwu9fRNdJtpVzTxY\nQEIL137nnXdyDs0RR+S70l9CCqGM/gwbNizH0py4jwffdkOO07WEAe49aNCgnGdOz/hU38oRUYyz\ncScemq/x48fng249eRDRd++70kaCmf+fP39+frcq5HLu/l9/bSwCbkTGPffcM0MQn+VUjOviWk2z\na6utlViLkJlnVl1EiJLmmT17dgbtPCHRBM1VGQM5oJI0wKBBg5I68m5Vr+3YIMjJO/oc77fiiitm\nmoFo5P4EljIyYxjEDDRSAcSOO+6Y14b0DHVW3UUsRH/RsV133TXTGtqLtkJ5KRK01thBBsLfqquu\nmkwAirs2Uadqrg3BFKaU356IfRgr/wcZpYpUb+mj9Ni8efMSGYlU2IVQAu10nrTf9REqtmvXLs9F\nh6D6qEjFKa0RRTrP/YUdUPzrX/96MkztVbRjOymxDNPYZ599IqIIDVdYYYWcE8xCCKRIBps766yz\nIqIo+DHntvm2b98+QwprC0vyTnMVaF9kNTLXVlsrsRYhM94PdQToEHrWrFkp/EAoAoD0EvmdAAPB\nxRy8UkSBvOJBsRqPBd0JGOJFyNKvX79EZJ6Q6ER4KRv0FIfy5uL+Pn36ZCGLIhHsQZwJsTEOiAOZ\nXn/99RTUxKK0AWMAzXhzpY36hTEstdRSKezQGfQXAlcNykoNuhZEXHHFFTONhmXRIIwPNCeUYWbl\nNz5aK941DV0VkUAoGgpElZbDOAYOHJhjh5GIS8tHDjPsjXglzSQenT17dvZHebI1CsWlS2kn1cKf\n3r17J0uRYpKCpGcQzfzULyzGOrc+yn+jnSzq0Mn/ZDUy11ZbK7EWITOkUIjAE0PXMWPG5NvxxHtU\nUwe+i+1snnAAmhTS7373u/SikJi6574QCjOgPvKO0hzPPPNMxl6KOsSn4qayVXcnVVH91ltvzRI7\nxQnaJM5W9ABNxVRU3QkTJmTqTcxGjee1IR5EEtPZ6ABtpk2bln8TI0NaiF01iFl95zLGNHbs2Cy+\nwcC0F/r7qX36Aelef/31ZD5V/QG60UWsHffHriDWE088kTE6nQNzWpTaixG5LtaAzT333HMZWkFE\nqQAAE5xJREFUYyv8sXEHm3ENKIsxuda4ceNybYrfoTv9hpqPBVhbCpwwxEceeSSvgWlaY1Jhi2s1\nMtdWWyuxFiEzr0m5PeOMMyIi8sC1Tp06ZSxULdMT14qdIQpl2ha49ddfP5GQeiiGgHLQRXmda/GO\nvF+HDh2alIlGFAfFUXPLpliAMlkt4pg0aVK+rVDRCXSApuecc05EFPEPpuJ+bdq0ydiPJkClxUh8\nV6wG5bAYCL777rsnWjmiFktxj6pBJWMHfZV3Tp48OTe2VF8tpLDHiwToBdiW3P1GG22U8wxtzB39\nASOAguVDGF0jYiH602G8+9qLFNy3bJBRDG5ziC2rPXv2bLZf21wyTIQijc1hiI888ki+OZKe435Y\noXsYM6+ngfJi6SWWWCLXs3JYn/Vzca1G5tpqayXWImSmRMozy78ps/va176WyrZ4SixECaUUyuHx\n4Erspk6dmvES7yZG82Y9cWn5ZWARxcYP8XHfvn2TIdjEIN5e1MZveUttEXdRsHv27JnbL/Xd60cg\nAgVSjKbEkbd/+eWX87vi1nIpZfmne/H+0BOi9OzZMxHNq3QgIHZStZNOOikiCpUZUkL4Tz75JGNF\n97ElT0mu+TE+EAQbePHFF7NsF2Oh9jtOllKsuku+WSWduV922WVTmVYTAO0cz1s2cab15vrYzy23\n3JJzJGtQVZr1G3pCTmu5b9++eQ3Xlw2glWAN9BCsS9sxk1VWWSUZkBfxYQTVl/x9kdXIXFttrcRa\nhMwUObk13gWSrb322unFeUK/QwTekJLoIHtx8W677ZafgVhURnGK3KSfthtCe+18+umnMybjQSGW\nje1lEwNSWmkDEHTZZZfNz6j5pfCLa3lV7IXpy/rrr58bVcTE2gJdxezQE8vBYrRvzpw5WbVWVXbL\nlW1l86pRLITeoE1Dhw5NNFGRRImGkOYH2kKQchUcNb16tJOshdhYXphVq67mz5+fOfFqBaLfy6Yq\nTVvF3tT+k08+OeuiaTL6iT15Za1ct2thgn379s02YIGOuLIOZHrMlbjfXFr3Xbp0yfGTRfB/FPHF\ntRqZa6utlViLkJlSp1JGrtaxNz/72c/Se8nD8d7iKR7Z61p4V3HLlClT8lga8Q8V02FvvCBlUJ2s\nOIYnf//99zMOomLLHTt4rWwUSSgnRoI4HTp0yMo2zIIqDNm0hYpNT4DoG264Ycan/uZl9VDF/WkD\nPLUY0a6xtm3bZryl7xBR7CbPzsSmGJN4V18fe+yxrJOXYTDPshnyoFC2dIpkRCxEI+xIPl5f7HiC\n/lgepiMeN1/rrLNOopo2V8dcJV1EgcDYFA3HWjnnnHNy7dFPILO16EAFNdry6JT5t956K8cbetI1\njAnTv+orbtQKLLfcctlG8+qZ+bwqvs+zGplrq62VWIuQWeUNb+sIGC+h3meffVLVk5vk3SCUo3jk\n/cRfkGTMmDHNXthFKRa7iG2gkphZfpQavMYaa2TOlhcX5y9K7dUWnlJFmZjm7bffTpWSZ1ZjXt1b\n6xqQHLo9/vjjiXBYDKUTOlLv9Y+5RvncaoiHzVCYxehVs5fXvfXZnto77rgjY3PoSW+gxGIf1G0K\nNEb0wQcfJCPAyBw9JE9/4oknRkShD/zqV7+KiIUxbUSBlh07dsx5MMYQ1Topmzw6duNII/fp27dv\nMwQW55pnjNBaUeUnxl511VUTPX3WAYricZkHLAK7MC/W0bXXXpuZFcxMhsHvi2v/TzSbEQEUV8yc\nOTMXh8mwQJXCld8UGFEUIKA+L730Ul7PljSpoREjRkREIXxxGCiVwnvpr5VXXjlTRw7bR4sWVcRO\nhDMh0io++/bbb2fpncXPwZg8D4uUFOHHuNx44435N6EFkcj2ORMunHF/QhRHtN566+ViMVYWPNqK\nMrMqzUNdbb9cbbXVsq1oM+pKvDHOHEJ1e+ktt9wSV111VURE7L333hFRPMQWrnm3mYPohA6jmLvs\nskuCh5NPjTUAKJ9zxnnoj/HQ79mzZ+eY+YyHmQDljGvz48ElNv74xz9O4dC9OW/CL8dQfegJshx4\nx44dc915wP1ep6Zqq+1Lai06A2zkyJFNzpVGf3mdZZddNj09tEFpfIZYRtL3d1528ODBibTnnntu\nRBS0SroCzSb7o3vVjRETJkxIT4+yozs84+WXX57nK11xxRWNiCJ5Tzz71re+FRELERv15XGFHlgD\nmkc0U04qvFhllVVSaJP6QI0hMREF3YUuaLbxWLBgQaYFMQWCFgHqtttua3J+1LBhw5qcK41CQ4Op\nU6emSKUPygwJQVAJYtrSaWy33nrrHHdtr56kCeWESMIgJaHGqHPnzomq2J71p83/t717CfGxfeMA\nfi+8yakh5yTkLCkLE5uRBoUcy5IkpRGxsCEbm0FSTBFhUKIshIUUIhumlLBRCqlJDjmzcJp3oc/1\n/OaZ+ff67f793Ndmel8zz+G+7+f6Hq7ruZ9Dhw7FPdrbnRFoHMz3uHHjgrWQKIxIzNPfYJXlL14s\nW7Ys1h4j1PqCppinYzN+IbgxXrt2bZyXfDEm1tj58+fzvtk5cvxNUZVmhhyQj86l4V6/fh3ITG/S\neQcOHEgpFQ31dBcjjNZ5/PhxZCQGhGzm/F5aUCqgU5gdWinHjx8fLzPImLSzzFgZdBwU1c4HoaZM\nmRIb02mbpCsZIPQWxKQFbX44derUeGFCgwlULV+HrO8Y5V1JR44cGS9KGDMlsXLTisDEmGz8BWNZ\nV1cXyA8BlUyU8zAKSIVJGachQ4aEWUR3MkBpe2wK6rkOTAFzePv2bZSprAdtrphbZSi9KVc5n/lu\nb2+PtalNE+Oxruh4r9i6Rszj3bt3wbj8DQYCsTFTyGxeXI95ePLkSawzm1QoRZb9jv+KjMw5ctRI\nVIXMsgqntrJ5IaXfGxL4kgG9ByGUcJSxIDKtoe3u8uXLoR2UcOhSTjINJbMq1UBN2XHgwIHRaOIn\nN5tmqwzn4966ZpnzyJEjcS5jwfkWGIDygn/nYo4dOzbYivHzmh53nl6k2Wg8iFLpqGv5lM2hvPEt\nh7nDhLQdipaWlvA1vBJqowlog+1oDKKZaf/r168HsmJV2JymEOiPhZgX46cMllLR5qoSAgV9crUy\nlCexONdkbt+8eROuuzWKUdC51qhxoPf9/vPnz8M3sDaMgbnFULEbqG5OrYcRI0bEWjT/7pO7/qeR\nkTlHjhqJqpBZ5pBlZEhZplIP0mQa6WVGLYlQRo3P5gGNjY1dNmNTD5T9Krd0rfz/ENxrdqNGjQqt\n4iUNqN9d0MFccYgEJWbNmhUZHwLStXQjncPple2xlz59+sQY0cB0ngYXmlglwFhxcyHi5MmT45rV\nos0N5lAOVQPNGZop6Mb169eHJnYd0JxmVTPW1mm+tKkuXbo07du3L6VUbBeltqvfwLEwBAi3adOm\nlFKxRW2PHj1ifjESc9hdJUbjCn1vLrnbY8aMievkM0BvTRqYgMDUuOd9+/aNFlYs0VxiHp4VDTXu\nD3Ndv359Sum3t+KZsFaNO1aj/+C/IiNzjhw1ElUhs84kbjHEkqEXLFgQDjf3UMcPDQXR6BTIXPl5\nGllUzVRHmJ/0CGYg+0JJ+uvChQuBVBxvNWptppVBx3Gz3YMXDtauXdulxdG10sjuUzsjBFJXr6ur\nizGCOPSk+qLuJwhiQzstm5UbEJSZEPTmIpeD1tu/f39KqWAO0GD06NHxmqRXMzEgepSmg4wqE9bH\no0eP4prNMy1sjGl65zAfEF09/+vXrzHfnGObB+hzqAz15MquxJQK7+b79+9RXzZGNt3AhFyjY/k9\nlZinT592+e4y19rc0c7QXhVFHb3S9zDv1q05xEz/NDIy58hRI1FVB1hra2un7hp1MXp42LBhoZ/V\nICEunaX+x+WTuSB4e3t7aCJZlU6lnelreo9e4bZiCsuWLQsk0oEDZWTZo0ePdvkKJP2pE8wWN69e\nvQoU1SfM8TYmnHT6lwNa+VVE9XDIzPF2jTt27EgpFdkeqpe3wK2vrw80KdfijcHVq1c7QXRzc3On\nLj5bBEGanz9/Rn1VbdwWQBDK30I/fgDteeTIkZgL82ru1Jttio9tQEvj5Bz9+vULNgft9OrzKU6e\nPBn3uG3bto6UikqH+TBmo0aNCm9FBUCPAJQts4VyT8KNGzeCWRhnzMxHFVtbW1NKhfNPS7tmbHLu\n3LnBWswFRgrl9+zZkzvAcuT4m6IqZN6wYUNHSgViyE66eaZNmxa1Xp9v8VNG4prSI7bphdA9e/aM\nWq5ta7l95dfHuIz0iJopHTh8+PDQzLKda1c7nD17dmS9FStWdFSehyPKkW9oaIgMC/G9yuf+dAvp\nipP1oeugQYOi2wm604BcY5ma3sYUvNYHjT9+/BjHdR7dS669qampU1Zfs2ZNR0oFY9i4cWOnv5sy\nZUoc0wfLbEWLoXDfISXnnNt76tSpLm9HQUrHMA/u0TG4xOZg/vz5gYzYHs8AY5g+fXrc48qVKztS\nKlx97jFd//79+9Dx6s2cc2tRN5yqAQ+hsvNOhx+W6E0u92m9YRXlt8ewn5aWllgzvBTPBu28evXq\njMw5cvxNUZWbrUapHkZDcW7v3LkTbjEn1gYGovxBOVsArVmzJqX0O/uqFXKMZSjIJXPatI7WlBV1\nTDU1NaW9e/emlAo9J6t392K7UNctf3L106dPwRZsUAgR6Xu/S6vJ3D4x+uzZs8jENnLgntJfjiW7\nQylegnlYvHhxuOvGhEvaXYdbSoXPAHUhB9+jra0tar+6lVw7tIOIfALH9L7zP//8E/+PZ2JcaGb3\nzmPhG2Adfu/FixfB5jAUmtY16x5MqeuH2bAZaPfy5cvwS2h9c1n+yB/GZz3xR86ePdtlgz7zYI70\npkNk73erOuj6W7p0aehnzw7W4v7+NDIy58hRI1EVMsuysqgOKRlrxowZ8RYRVIHAMpKanr9ZtWpV\nSqlAw8+fP0f9kN7SZUNLqztyUyEbR9GxW1paQofowFG703/rd1Mq6qa0uPqfYwwYMCCcaJpYxqcX\nnYdrTu9zm6dPnx5IS4sePHiw0++op9LWEJDeVOe9fft2l0+5Qgr1TMxBeFdaTR4aQJYlS5bEBorY\njN9xbAzIdZk7Orx///4xJ+rg6sfm0jrxBpSeAWyP17Jz585wn80dr8Y4VO40oq+dB2AesMd+/fqF\nPtdJaL3xfrjIrgXL0um2aNGi6B7zU13c/fFUnIubz+9xLxcvXoyavDHACD1f3W32311U9TAzZgwQ\nEe/mjx8/npqamuIiUyoWJFqCylhMKAV6WF9fn44dO5ZSKiixv0HFNTxo0WRkeBjR8nnz5gWlMujO\n192WLB5M1M9EuIeTJ08GtVdSQevQSEYLk8WkGqMJEyYEBdOc4nU6yUPLIzPRZPueFLmxfPnyLjuk\nSrT/a2dHX3qQbNFxD+jhw4djPBlhFhMjyiL332iuY06bNi2+8cxUQtmZWK7XOpGYzQGjaOPGjUGV\nlY7IAK+QVgaaS8qU9xz/8OFDzJm5dG1+R3IwL6SIh3rixIlBm8lG7arkgS9ilvfAVrKSoHr37h2J\nz/GdDzj9aWSanSNHjURVpant27d3pNT1FUgZZfDgwZH5mRUokRZQjRKQw1cgZfKtW7eGwQOpvCYp\n28qgDDKUBSJrgLh06VIwAgjJmJGNr1y5Erb/7t27O1IqkAfthRZtbW2BLK7fT1QThUa7GCDo94AB\nA4I+oa+Yh7EhTSBkeY9m5zp37lxQMvQNFYTuu3bt6lTWaGlp6UipMLWUx5hKX758CVahXdfumOSA\nc0E984AlDB06NMZJicycQiQSg3RT5oLCzn3ixIlgRqSE0KJ57dq1uMd169Z1pFQYj5gi9Lt//36n\nDRFTKtYVdugaMDQSSkPOnDlz4v78G0aG6ZAgJJO50xSD3T5+/DgMZeNX/qb1mTNncmkqR46/KapC\n5pkzZ3akVBhRZXOhrq4uMpWCu8xPWyg9aBZQhlKOWbRoUWwTQ/8wcaAQvQuxvPKolU7r3sCBA8PM\nopUZRlC3tbU1st7ChQs7UiqQks6WsYcNGxb3B+FdiyyOHUBPqK5Vb9KkSWEC0tn2lIbqyioMHq2N\nrkuWf//+fSACdKFFafqHDx92yuqbN2/uqLxO7AdCTp48OUp9tCUjEppDHxqWt+Ee29ragrFgbZp0\njD/EYhhp+GHEWQ/fvn0LtgG5/A5T6d69e3GPW7Zs6cSusDZo3NDQENdE52JRNKp/5wlYd9D2wYMH\nsfYhbfmrj86LhWk80oBijBsbG8Mk1Hhi7XgV9ebNmxmZc+T4m6IqN1sGVp6hs7iKV65ciWwiA/tS\nAe0KkaE71OEc3717N9BMcwJ09+I/VPUihJcfNAHQordu3QqtVHZvoUplYBiyuOPR25cuXQq0htBe\nEKh8xTGlAmWhKeT+9etXvGziWDQSnas0VL4uSK5xBYKnVLjBxte2xOWARpoWIKNjHz58OMp1PBHf\nwsJCOLSQ2vW71zFjxgQTUvbxt3Qn9FMi5J1APEj948ePGFPn00xBs1cGNmENGVNr4vTp03FtWIy1\nylmHxOVtjDX19OrVK/SstcETKPsH1pm1W16Hzc3N4atgWZBZi/CfRkbmHDlqJKrSzDly5Pj/jYzM\nOXLUSOSHOUeOGon8MOfIUSORH+YcOWok8sOcI0eNRH6Yc+SokcgPc44cNRL5Yc6Ro0YiP8w5ctRI\n5Ic5R44aiX8B0gqoqGWWX4EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1969cdf90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 250, D: 1.376, G:0.7614\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nOSKiSBBf5oiIIkF8mSMiigT/C7WTxXV4owxlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff196977b10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 500, D: 1.332, G:0.793\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nNpKRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1972949d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 750, D: 1.314, G:1.014\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEVEn+P/Ki5u7902VtgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1973b97d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1000, D: 1.275, G:0.7455\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wN3oSC+7RNvjAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff196eb8fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1250, D: 1.255, G:0.7701\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztnXeYXVW5/z8zCUloBomBS0JPgNCkd6kGRKU3xVCkKyC9\nh3KlWIDLBZHeQaqAdEkElA4XpPyoUkILvUgICaTN+f0xfvY6s+b0MjPMrO/zzDNzzpyz91p77b2+\nb39bcrkcCQkJ33y0dvcAEhISGoP0MCck9BKkhzkhoZcgPcwJCb0E6WFOSOglSA9zQkIvQXqYExJ6\nCdLDnJDQS5Ae5oSEXoL+1Xy4paWl14WL5XK5Fv8uN78555yTKVOmNH9QDUT+/KDvrOHss88OwFdf\nfdVNo6ofLS3t02pra2sp89H2z1cTztlXboQYXtTuDn11HLPNNhsA06dPL/udvvowf5MR32/xGhZD\nErMTEnoJqhKz+wr692+/LDNnzgRgxowZQDsj1srO+butf7e2tu+lc8wxBwCTJ08ueQzPXYiR65Ue\n/J7HSSiNb3/72wD8+9//BhorvdV6jMTMCQm9BL3iYW5paWkoo8ycOTNjZWhn6v79+1e1Y8Zj8vUy\nyyxDLpcjl8sxa9YsZs2axeTJk0uy8tFHH83RRx9d8nweUwwYMIABAwbUPN5vOorNp1+/fhUfw3X3\nWKNGjWLUqFGcdNJJTJo0iUmTJmX/i69/peMZOHBgxeMph17xMCckJHSDNfucc84BYL/99uvwvjtm\na2sro0ePBuCss84CYI011gDg66+/BoK7oRF6SqMtoWPGjAHgxhtv7PD+oEGDAJg0aVLVx/TazJo1\nq+rvJmt29VBKuvDCCwHYdNNNAVh88cUBePDBB3n99dcB+Pvf/w7AbbfdBsC0adMcB9DZ81DLvVqp\nNbvLH2aNPhMnTgTguuuuA+Dggw+u+lje3IqTCyywAACffvopAGuttVZ2sYuh0TeC85t33nk7jKWa\n6+wNoKjfqM0Ket7D7PVqa2ur+Ri1rqGbpMasqVOnArDzzjsDcO655wKwxx57AHDZZZcB7Q+7ZHTc\ncccB8NZbbwHwX//1XwC8+eabAFxyySUA3HrrrUAwrvqwDxkyhPfff7/De/F6J9dUQkIfQ5cz8x/+\n8AcAfvaznwEw99xzA4Fdjz32WE4++eSSx3DM7ubf/e53ATLRx93v2GOPrcRwVBczxyKwO/PWW28N\nwO677w7A2muvDQQ3Vz40gjif+eefv8Ox3fWFzF3oWDGawcxe39i19vnnn5f9jtLG4MGDgdrUjhil\n1rDUtfK6OyaZ8ZNPPunwHVUk31988cWz+Vx00UUdPrPDDjsAYb0feOABoD16MB+ea8aMGUUlL4+9\n5557JmZOSOhLaHrQyNlnnw3AQQcdBIQd6pprrgHgV7/6FQCHHHIIAKeeeiqfffYZAPPMMw8QdrHH\nHnsMgDXXXBMIzKWuLDuqj8sYtaLQru57nsvdXePcxx9/DATjyauvvgqEeX/xxRcZAzuv/fffHyCb\n99VXXw3Awgsv3GGenlNGbBZiFo11ufj9iy++GIDtttsOgOHDh/Puu+92+IzX0GPIZM2GYy2km2us\n8rqvuOKKQBjzyJEjAZgwYQIAiy22WKfjXnXVVQDcc889ALzzzjsAPPzww0DQw+P7ZvnllwfgxRdf\nzD4TY6+99gJgzz33rGiuiZkTEnoJGs7M8a4u837nO98BAsu89NJLAPzrX/8C2vVbgBEjRmRm/I8+\n+giAv/zlLx1eL7TQQkDYsR566CEg7LTiwAMPrGsusZ4133zzZcwrw7jjHnDAAQDccsstQGDV8ePH\nAx3ZTReHu/i4ceMAeOGFF4DAWm+88QYAo0aNAtp3ceg8z0ZinXXWyVhFDBs2DICbbroJaPcSQLB/\nHHnkkQDMNddcQLv04dz23ntvILDfJptsAtRnoY/vsVLIS1bI3vviiy8A+Na3vgUEG4X2jfnmmw8I\n13nIkCFAR3b3eA8++CAAp59+OgCHHnooECQ1702PqZX7ySefrGiu1SAxc0JCL0HDrdnFfGXqzGee\neSbQrlcBLLjggkDYBZ955pnsO1o8n3/+eSDoxjKz/rlYH6rGd5lvCe3fv38OSgdnqCOr88hGWnKV\nNGRVrduFoJSy2WabAXDzzTcDQUeT5d9++20g2B+qQS3W7DgR5LzzzgOCHcC5ad1Vl5R18nHSSScB\ncPjhhwOdwxePOuooAH7/+9+XnUsxVGvNlpFlaNfBz8qqlcB4Aq+F3/W3/9dbo9T5wx/+EIC//vWv\nZc+R/MwJCX0MDWVmA84rgeGORt/8/Oc/B9r1SHUi9YrlllsOCJbBXXfdFSCr+qFeWguq8TMPHz48\nkwYckxbQRx55BIB7770XgNVXXx2ADz/8sNNxZDwZzfkYTeQ1lE206iu9aBkvlzIZz6+SOY4aNYqX\nX34ZCHYAdXmlqx/96EdA8C6ss846ReeobWSRRRYBiicW1JPk0R3FCWTzf/zjHwB873vfi8cEwLPP\nPgvASiutVPO5EjMnJPQx1MXMtcTVqjvIcDJzvs/VKJrVVlsNCAylDv3ee+8BwcpaT8JFNbv6oosu\nyrrrrgvAc889B8Bpp50GBKu91m6TQeIaVPnFCWIGdr5KJNoGdtlllw7H+vOf/wy0R08V81EWml8l\nc/zss8+y8+qB0GJ7/PHHA8EPrq4v+6jrFxkHEKQJI/88h2ur3l3NPVVqDQvdG+Xu22KJLd67M2bM\nYKeddgLgiiuuAIKOrLXea6ZNyHu2mYkWiZkTEnoJujw2253q//2//wcEZtYa/OGHH7Lkkkt6PgCG\nDh0KBMuxu5/W1XpQrb4lI6v7aa309yuvvAIE37C6Yn58tRZu9Wkj1Z5++mkgsNT111/f4fXGG28M\ntPvioZ2py1WhrMWabVTTRhttBAQJKO+YQGAqpZX8DLV99tkHgEsvvRQIrO36G5MtQ2+55ZZAiGXW\n0lwJmq0zx9Fbc889N6+99hoQ1k7pSku51yg/tRdqyw5LzJyQ0MfQZQX9llpqKSDEsKpr7LbbbkCw\n2Pobwm4na8tcHqua7KFG4Qc/+AEQCrmtssoqQIjiMtLJHTvOeAL44IMPALjyyiuBENus1XiDDTYA\nYNlllwWC5f83v/kNUDi+uJHXQh1ddpElZVH1Q4tIxN6E1tbWTFLQr+qYfa1FXj38rrvu6jS3GF1V\n8riYTcNrvPfee3PEEUcAIa7eSK99990XCBJcI/K1Kx53V4vZLqI37B133AEEg5iBIRDEGt0/Y8eO\nBeCXv/wlEFxVGo7iMMRKUI2INvvss2cLqyFHMcobwNBAH2rFYB+AXC6XqRY+JHECg2KtN4JJ8Uss\nsQQAG264IdDuxit3k9STAqkoqVgvdCMaZut47rzzTqB93RSjFbd1a+myM2TVzUgVSjFVg1ElaLaY\nbeDLiSeeCLS7oXRJmUijmuXaGkTife5GqDuvGiQxOyGhj6EqMbuaAPdikG08huGdps+1tLRk4oyu\nD+srGUaogcYiBiY11MLM1SB/3jKyv3VF3H///UCYl6K0jDNlypRMBJVVzz//fCCwu1KKjK0Ir0FK\nCcUkhnw0UqyLU0iVlFQL/K1BUjbaYostskQLmUuDoIhDJhXZDbqpte5ZM0RxQ00d82yzzZY9C0on\npiu6tnfffTcQDKWF1K1GIzFzQkIvQZfrzO72q666KgBffvklEIw9f/rTn7Jd1V3NIAZ3e3c5dWUN\nNqecckrV46lV31Lnc/xxcoKGPOd56qmnAu1hoM5LXVM2yhuHYwOCKytOfSxUcqdcn6Ja1lA7gcyk\nfvu3v/0NgO9///tAx6IJ/m3aqsEhMeKijPW6bhpxj8bX0JRV12vq1KmZ21CbiGvxpz/9CQi6svPT\naFuJVBu7G5POnJDQx9DlvaZ0TTz++OMArLDCCkDQi9dYY43M4qdeomvKgAwTvbUoGmTSLOTbCvzb\neay88spASJpQN7z88suBYJ0/5phjAFh66aWzZHcLMhRLMpAZTAuV5S3fC0FCyLeW14JSurY2DOGa\nyU5CCem4447LrovW3WKQ9V1Dkzy6EzEza733uo8YMSJLILG0kNbsH//4xwBsu+22QLDvmJzifV4K\ntbahTcyckNBL0OXMrM6g79T0P/HJJ59kO6MpjlpJDRvUcqyFuNE9ktRp1VEd89xzz535l2VoAz0M\nErD7gVbs22+/HQiF1W+77bZMnzZY3//J1O7M6623XoffBpvks2exRPpy1yS2Flejq8Yhq9pBvCYT\nJkzIrous/sQTTwCwzDLLAOG6afdoFoxr8F569dVXs9LMSldKGk899RQQroW6suuv5LHyyitnJakM\nGjJe4tprrwXCPeQxTZ6JixRUkzZcDomZExJ6CRpizS7l21MX00Ln7q0VuJQfUX3Q48t+RiSps/30\npz+teA4x6rWEOr+4cJw6lPOV0b/++uts17YljyGAJiGIrbbaCgh6lnq5/vZK1q6729MoATh/7wOh\nhVj7Ry2oZA1NVhk6dGiWsqkEpE3GNjSm4P7v//4vANtssw0Q0lw/+OADDjvsMCAklyhpnHHGGUBI\nMDFJyIjAOM4CysdvJGt2QkIfQ9P9zDvuuCMA9913HxDKtKprGO9aKEFAq7UF/dzlDGq3XE09ReHr\nZeZYKtEH6/uxZXLgwIGZDmyEm7qY37XIm6VotA3UEt3VXcxs6ueiiy4KhGKFSiyyneV7m72Grsc6\n66yTlUMyaUZpwTH42+9YcEIG3XzzzTO/8gknnAAEW4BrKPsbk266q7p7obEVexYTMyck9DE0nZm1\nHMom9lzeYostgM7tO6ZPn57tlDKWsctC3UVfXxxBVQ0aHT1ULKY4f/e137Q+SH2Vwqwprdf1pDd2\nFzPHfYljKG2oSzdqjv369ctBcellwIABmW4q4yot5B0PCF6UuJDGqaeemn3He9NyyLbliSXQf/7z\nn0C4D/JbFJV7BhMzJyT0MTScmS1tYxECrXhmNpnD6+4YW3tnzZqV6R1xczb1T3c3c0TryeLqjjKt\nSivqUf52XksvvTQQ2tEI/esWKRg3blzB9iv56C5m1vNgs4OY/cymMkdbGAmmL7sSVLuG1113HRC8\nIF47pUT95pY+Np/5ggsuAOB3v/tdxsBx29dyBfSV3GTmWjwSxZCYOSGhl6AhzFyJvrP++usDIdNG\nRi4VqaSfT3+s2VPqOupj8RwK6a3FLIa1MnM9ebMyc8y8ceSZkWKWKHI+hc6tNKP/XnQHMw8fPjzL\ncLOljrnmRsTp95Udzf8uhWL3WSVrKOMrEUC4vvqZtcAbO282mPqw7YKmT59etBFBsfvCzDftIOrf\nrm0pVMrMXZ4CGcMEe8M6b7zxxix9zAfesEcveiMTz2t9mFUbXOhiqKaPkS6R+Eaxe4YuuvxjFwu6\nMWxw2rRpNT/McehhMVjGyWSCLbfcspNqJLwOGjlVu0xM0FVVDbpDVepKJDE7IaGvIZfLVfwD5Jr9\ns8suuzTsWP/ZpUv+5M+vX79+uf+4Npr2M3bs2FxLS0uupaUlN8888+TmmWeeXGtra661tTU355xz\n5uacc87s/XfeeSf3zjvv1HW+7ljDXC6Xe+WVV3KvvPJKbuTIkbmRI0dmcxw2bFhu2LBhuUGDBuUG\nDRqUmzlzZm7mzJkNm6PvzTXXXLm55pqrKfPLv6+qvWdc+3rWsNhPYuaEhF6CbteZuxtdrW/lhy3W\nWnSvGuNbdxjABg4c2KnmdDNrXSeduR2JmRMSegm6vDhBX0cjSuA2u6NDvYgLD/Z0NKKEdFd12yiF\nxMwJCb0EVenMCQkJPReJmRMSegnSw5yQ0EtQlQHsm2L2j2OcS6GvuTWcY08w2DQK3/Q1LFdBplLX\nVFUPcyVla+IkB2+avFjhak7ZAZXegIXOYeC/yRp9HT39IW70ZtOIhnqNHJPFGm+55ZaG9W5OYnZC\nQi9Bj4wAszhanCJYDpXsnGPGjAHg6quv9rPfaBEths3eLXhQaQRYI1vBFkKlGVi1oNAaVtIStlja\naDkMGDCgKfMohhQBlpDQx1AVM88222w5CLtdPbqDJX/i5O5mw3xZS8TstNNOvYqZZda84vzdWgS/\nUngv1dJqqF7pSmnNhunm0zcSjZpfKSRmTkjoJeiROnOl0AVlZQ6LB1aDRuvM5XTPDTfcMGtp8oc/\n/AEgK8reDDSDmb3eNlL3tc0Ad9999y61ljfL7mGzN1vpKkUutNBCWXlkS1vZ1LAY4hJF1aAprqnu\n8k1a8dOHdcKECR1ea+yoBM2eg8e1G6C9fe1kMHPmzOzmt8qmaYJuTm4EltaptV9vs7DJJpsA8Oij\njwLw/vvvA6EkUv/+/bM55NeHLvS6J7vIfIiF99miiy7KrbfeCoR+zJY/0gDperu52wGjmfNOYnZC\nQi9Bjxazda+428Vw7HaAkCGq6Y7QaBFNdjWdzmJ8Fqw74YQTshrSdkyw5nIc7LLAAgsAYV61oBli\ntjWtrWap28n1yC/A4N9WobSThXOz+6O9noWfk/EK4bTTTgPgsMMOa6oR8/DDDwdg7NixQBCZIbja\nvOeKwS4mrrn9xJZaaqmi38mTZpIBLCGhL6FHMrN1i2OmdVf7zne+A4Sk8lKBAaJYAnqzg0Z0c+T3\nH3a8cefDuJZ4PcnyohHMrI6v7i4bOTcNeSuttBLQLmk4F/s0WZp49913BwIzWQM97vSgNPbJJ5+U\nXd961/CUU04BAvMWOH61hyyLiRMnAu01xuP7IDaWJddUQkJfQ6NL7d5www25G264IXs9ePDg3ODB\ng3Ozzz57bvbZZy/7/dbW1tz222+f23777XPzzz9/bv7558/Kk4pKxlHpT7XzmzJlSm7KlCl1nXPa\ntGm5adOmFRpLU+dXyRxbW1s7vefaffLJJ7lPPvkk9/XXX+e+/vrrbG393KhRo3KjRo3KAVkp3YED\nB+YGDhyYmzp1am7q1KnZZ8RHH32U++ijj3JtbW25tra2rCRvM9ew2M/YsWNzY8eOzZXD2Wefnf39\n1Vdf5b766qvs9eTJk3OTJ08uewzv6SOOOKLqNSz2k5g5IaGXoMfpzPn9avVbaiFWdzYwXitwPch1\nY6JFrDvXEupXDrkadGZ7CRveaK/hrbfeGoDRo0d3+P9FF11Udhxa6mP9cPnllwfg2WefBcJaV4Nq\n1zDOd/e62/fK/ljabrwfhw4dCsCnn37a6Zh33303ABtttBEQbAW27NEzU+zclc6vFBIzJyT0EjSk\n1G4jo1py7W1igLC7rbbaakBg6m222Qaozp8c44wzzqh7rLVCS2+MG2+8EYDtttuuK4fTCausskqH\n18888wwA55xzDgAPPPAAUFlCgmumFKJPWqnKhJdll122w/dMiNl1112rTlEsh9ifb2fIAw88EAiM\nLEqxp2vpMf2tXzn2SPz2t7/tNJZapJFCSMyckNBL0ON05tbWVu68804ANt10U6CzD3LHHXcEQvxz\nPehqnXno0KFZgoKQrZQw6pE4YtSiM8ewl/IjjzwChOIRrofjf/PNN4H2RAT163PPPRcI/Yllubg/\n8a9+9Ssg9G/Wdz1s2LBOMdIxql3Ds846Cwj3jz3DLVYQIy+dtNP/9AmbhFHMJ+53Zer8GIliklre\nd5POnJDQl9Dj2tMMGDAgY2Thrufu3ghG7i4UYpk4XbIRjFwPZM+jjjoKgKeffhoIBSVkH7PX1Hvz\ndT/10L333hsIjCv7mfEmKxlVNm7cOIAsxXC++ebj5ptvBoKtpF4ce+yxQMhkKna9lRocc6FCGsVS\nGrX3fPe73wXCtVp88cU7fK6lpYX7778fgPXXX7/ySRRAYuaEhF6Cmpi5kTpdDPNAIVgGjQ3uDbjr\nrrs6vVdJbHm1aITPWh+pFlh9pZYrdn0KWWOff/75Dr+F7Oa9o1/W7CizzGT7Bx54IPNFNwqHHHII\nEK7Ryy+/DAQWFdtvv32HMVeD+FgPP/ww0J4LDUEPb21tZcMNN6z6+IVQ08PcbDHQBAvT5HobTC4w\nCKEZqMdNOMcccwAhxXD8+PEA/PCHPwSC+FnLJuTcFadd4yuuuAII6aw+aE8++WTDK4fG4nr84Cni\nv/766w05H8CWW24JhPmbSJLL5bj33nsB6n6ok5idkNBLUBMzxyF5jdgxDRL49NNPu42RDVx44YUX\nGn5smaalpSULpIhdVD0Fis+6lywT1AjoFtJA5LoL3ZDeY3vssUdDUkFFS0tLJ7H9vvvuA4IIbLmm\nRuLdd98FOhY2gPbQUYNV8scI1UtXiZkTEnoJGhI0Uo9BzLA+g/ndJfP/V09/qhjqeTJAVwWNGHgx\nYsQILr30UiAE9F9yySXNOm1dQSPqcrqZ9t13X6A2SSyuk+410MikEc0CFLohhw8fXrZsUrVrKNMX\nKwTpMxFLoPXg8ssvB0KAjYFP//73v7NiG/U2jkvMnJDQS1AVM/fv3z8HjXWl6JJw54Zg8dtpp52A\nYE2tB8X0kGYz84ILLgiELpT5Y8jXo6E5pXVrYWatqrKjOr4BEtb9rgePPfYYEBISxFNPPQUEC/Po\n0aOzzxaT0KpZw9bW1oyZi7nvXAfnXQn23HNPINQOVze2FO+hhx4KBOn19NNPB9qt+CNGjABCKaEY\niZkTEvoY6tKZtf4ZYN+/f/+KLY/uimuvvTYADz30UNHPNBNdpTMXus5dPT+A/5TkKWopXXXVVTNd\nXmaWMcp1bchHua6PSy65JAD/+te/Orwv+8qOldyf+XP88ssvc9BR0svHlClTMj96jJNOOgmA448/\nHuhcSKAU4h5fxhAYxuk5DYoy0aSSLpWTJ09OzJyQ0JfQbSmQcUkg0dbWlu3GxVLD4h7EtaBQgfFm\nMHMBHT07t9cg9mvGOnWd569aZ/a8MrJRWbJt/DnZ17DbqVOnZp6IuE2L+rheC6PJYqYqlxaYj2ql\nKxNI4kIBFkHQO1OqLJWNDCwhFK+z18bCGk888USH/+dfq3JIOnNCQh9DlzOzhcaPOOIIILQhic5T\n1znc9fKTNoqh0TpzbDW3wPoOO+wAtBd+MxG/Vv/8wQcfDIQOhKVQj5/ZVFRTEPXL2pbm7bffBsI8\n1BvPPffczALtd0w3vOWWWwqey2J6119/faXDy1DrGuph0OMgLOZvYUOTYyyTtOCCC2YWfT9bYExA\nkFrUf2uJZkvMnJDQx9BlzFws6ia2Ai666KK89dZbtZ6majSambXwy1rOz11+9dVXz/RCGc1dO68d\nScFjawG2cVslaETZINnF8WmpLea7Hz9+fBbP7XrHVtsjjzwSgDPPPLPDOWpBrWvo2IqxpTYCpSsb\nyE2cODFj82IW70Z6KhIzJyT0MVTFzEOHDs1BiJ+tBvHOHMe9NiMOuxLk73oDBgzIQWPytd977z0g\n+DuL+T2huQ24G8HMcdM9xxnHGYhZs2ZlEsmaa64JwAorrACEvGXnHN8XSisec/jw4WXHVy0zx/OJ\niyw4P0s8Pfnkkx3GfNlll7HLLrt0GK9FKM35LgelsenTp5eVShIzJyT0MVSVz1yMkSupBJGXpQR0\n9idaieHWW2+tZkhAdTHNxXQ4aGwFFVuYuvvLzF999VVmZa+0+Hk11vlaUch3L/tceeWVHT4rQ6k3\nnnfeeUBgqUsuuYTNN98cCLHW/s7z7xcch2tQCSPXilhHdh200jtGG8DL3HpeDjjggOw7zqNSRhaN\nLuwPXWgAa6YoWQ+6s9dUV6ARYnalMM1TN1Sz0VWBP/H5St3DzbjPk5idkNDHUBUzlwvSbwTa2toy\nsd2gCIMkmoGuZuZZs2YVTYpvBrqSmbsLfU26KobEzAkJvQQN1ZkHDBhQ1sxeygDVKFRTmrWv7erO\nsZbytaar2nOqp6DQGtYyP42WBvz0FCRmTkjoY2i6NdsSo81wNTTCclgvM+uusPxRIxEHN9SCrtSZ\nG12svlJ806Wrcgk3iZkTEvoYqmLmhISEnovEzAkJvQTpYU5I6CWoKjb7m2hcKIdqjCeDBg2qqpZy\nPhrpkqvG8JeCRnomqjFuVmoA67aCfj0F+ReqERFu3R2DHp+/3MPcXRboYnD8WnYrKexX6GEu9bBU\nuka1XJt61r+SRg2lkMTshIRegm/Uw7zIIouwyCKL0Nra2tCmXiKXy9XMqC0tLbS0tFR0jGLj79+/\nfwcm8pjFXhfCbLPNlvktS8FztbW1dWIex9evX7+a4shXWWWVTu859m9/+9tZWV2g0zm8fvG1qBYz\nZ84sycqVoNC1KXS8QsesZK1iOHevf7XH+EY9zAkJCcXxjdCZbe1hEQILj4t69JR8faRfv345aIz+\nWGxMsjd0Lp0kQ8WRQJaYsfiC3y80TovteY1mzZpVtwHMuciUtiAt12o1H3/7298AsqIFsSHx9ttv\n7/D/atBou0ctKHcPVmMAtZCFBQzy87VLITFzQkIvQZczs/qSbUlKwTJFjtEC+hdddBEQYlq7qkxr\nPqvGbCXLmln06KOPAoGB/Nxyyy3HM888A4RWLWYhKYHEJW0/+uijqudVqApHJXNsNP7xj38AoYB8\nM7LmGu2assSuElKpZ8Q1i4veO79YqlKayj9mOVb/xrqmhg8fzv777w/AbrvtBoSb2vpU1qsq15Nq\nxIgRvP766yXP16gbIb/uN4QexpbQsaPitGnTuPzyy4HQg3iJJZYAQj+iBx54AAgdJeyGEfdAmjFj\nRtm6Z13pZ3buX3zxRbYRxwYcE1LiTiauYS0PeVf7mWOjJIR79aWXXgJg6623BmDXXXcFQr8u7xPn\nOXLkyE6dMGMk11RCQh9D7bb/JmHSpEmcccYZQOhHtcACC3T4/eyzzwKdqynGu15sKKsX+TtyLNEo\nPlllVHYdPXo0ELr9jR49mu9///sA7L777h1+v/zyyx3OY1eIeF5WiyylXtTj1qkVXu9S6aAxI3/2\n2Wcd3lf9yjcO9pSAFpG/9q7vZZdd1uEzqk6qFf52bf3dyO4tiZkTEnoJepzO/Morr3D33XcD8L3v\nfQ8IxiR16TfeeAOApZZaCgghe/UaF+L5FfpuHOIXM42lZ2SYE044AYB99tkHaO/ru95663X4jga9\nZZZZBghCCY3UAAAZM0lEQVQ6tMaTcePGdfi8YygVoFKPASyeY9wPrMA5yh2yYqy77roAPPTQQxV/\npzt05iFDhgBhjc4991wguNa8R1dccUUAJk+eDHTuCtLS0sJ8880HFO83nnTmhIQ+hh7DzHY4fPDB\nB7Pdbv311wfCrrbHHnsAQZduhJujkl09X89ZfPHFAXjttdc6/G+eeeYBOrvcYmvuXHPNlXWocCeW\n8S6++GIg6NCNCHyo1prd2tpalGkbGYjhmjl3r5NrbUH9Ss5bLTPX2hdbXHHFFSy77LIA7LnnngB8\n/PHHQOj5rM3CtTYAJPbAzJw5s+x9nJg5IaGPoS6TZyMKzmmR/sEPfgC0M9sFF1wAhF3PHVRnvixo\ncEWzkZdO2Mn6KKPEY4n1Tj83ZcqUjH1GjhwJhP5a6ovFWL4rkM/KjlnbhOwi2xRLAjBZAMIc7Skd\nW3FdU/tW/fa3v+10rHqgzmqgDlTPyIZX5qdlasf5y1/+AoT72JgA/c32q4qDjfJZOJZSarVBJGZO\nSOgl6DadWb3lJz/5CQBXXXUV0L6D+T/DHWWExx57DAgJF0ZQPf744zWPo1mWUKWW2CLc0tKS6Uja\nBE4//XQgsNJNN90EhJ26Ft1Oxps2bVpVOvPkyZMzJnIOnt9kiY033rjkufMZ2w6R2js89lprrQWE\nSLlKjlUMzbZmb7bZZkC4V5daaikefvhhIEgUa6yxBtAedQhw8803AyGM0+8Wet7KMXLSmRMS+hi6\nLQLsueeeA4I+JlpaWjjuuOMAMt05TrW78MILgdA/uCdCi7zpgvqS99lnn2x+9vQ988wzAbjhhhuA\nwNBHH310zeevNflk7rnnZs011wRCpJ3tWmxkUCy+2pjx/IQU7QPqlEav/fOf/+zwOu5VrQ2lO2FS\nkLkBRuTNO++8WXMHE0j8rCy7wgorAIGpS0nAsR8/6cwJCX0c3cbM8847b8H3v/jiC37zm98AnXcz\nW7vuvPPOzR1cHVDHk71OOeUUAHbccUcAzj77bLbaaisgzE9Lq5FA9TByI3DyyScDYezGxJcrRyTL\nQtCNzzrrLKCzdKUOrU4ZM7MZZN0Jfd1LL700EGw2w4YNyzL3jPAzY8y8AiMBq0G9kXSJmRMSegm6\n3Jqt7nTNNdcAZPpZvr5gLui+++4LBGuiPkP17XwmgGBZnDhxYsXjaXTJmdiKLZtZtODuu+/O2Ftf\npPMyqsjsqdgSXss4ZsyYUXVstpZwY8hlai22olj5o0pw2GGHAXDggQcCQR+P/bC1ltptRAlhvQ6O\nQa/Dfvvtl1n2LU5gtpwxF9oKCpWNKvR+KVRqze5yMdtwN0VKL7oXYerUqVx66aVAEHN8eA1e9+H2\nQXHBqnmIC6ER4YrOw0XTEKaINn369CwZ3RvBoH1vCB/yeEOIg/TzEd+89QTyaDy79tprgWDEE88/\n/zwAq6++OhAMkjfeeCMA48eP7/Sgx2PW6GegjOfQiFbvWjYi+cMxP/jgg0BwJc4///xZSPGrr74K\nhHvS4BjVhDhEs5m1yZKYnZDQS9BtQSMGIhgGqViy1lprZUYT3ROGN8o2fldm09ji/8uV0slHvggz\ncODAXP7xCwXFVwsZ2p37rrvuytxxY8aMAUJi+6GHHgoEMdtAGqUYXUQWOiiEmKFrKRtkuKahinGQ\niMd2HF7/6DwdXnstVbM0clpWp1hgTKGgEVNjTZNsVtCI6obSwl577QW0p6TqajRwyWIEt912GwBX\nXnklEMpG5Y3PMVc8jhQ0kpDQx9DlzCxzWGLmoIMOAkJY33nnnZe5oO69914gGCK23377Dt+VwepB\no3d1WdzrqvSQH0w/ZcoUILhj1IkNWzXQ4L333gNCemh+skAxeEyNg/UU9NMQaWhiMchgSi5LLLFE\npjvG8HpYiMHUwTfffBMIDK07qFxBRmgeM3uvev+5pmPGjOHII48Egq6vIe/6668H6tPZvUZKPomZ\nExL6GLrcmh2HOapjqB9ut912WeK/4YJ+R4bQhSMj1FM3Ox+N6ODoMZyfY1cPXXLJJbnzzjuBsAOr\n41uOd/nllwdCQIKpoJV0NozddbXA8zgudVN11fhzMpiBEg899FAWaGJwkLW/XSvDIRdbbDEgWK/v\nuOMOIPSrmjBhQrd11JRdDee0fPDrr7+ejUmduJEFFEvZREohMXNCQi9BQ5m5X79+nYrqxdbVeNcx\nmdtyPM8//3zmV5aJt9hiCyAwljqmYY+//vWvGzL+mAHici6lSuoIdb78YgQQGGjbbbdltdVWA0L5\nI6+RrOr8tYBrzS9VOrhS9ionfbS2tmbML7s6HoNG7r//fiBIH/qZt912W6A9mcQgEC3wQvaO9X8D\nftS1//znP1c1r2KI9c9hw4ZlEl+lNhelCkskjx8/PrsnLL6oZNGdZYETMyck9BI0zZrtrq1Osd12\n2wHB2ie7+nqbbbYB2ndiLYVxCRkjp2Q/mboeVFPQr9S1iiUQ52CJXfXNmTNnZnq0aXNPPfUUECLB\ntPDK4E8//TRQf+uW/8ylamu2qaambFryxzgAvQwWHNhmm22ysapn6ivPG5fj6fA575tq+hLX2i/M\ndVB6ipsNKJkZC+F1GDVqFIcccggQdOWVVloJCFb5RtpzkjU7IaGPoeHMHAfdGyFjoruvtZAaXeMu\n+MEHH2S6mtbUE088ESCL2a6lK2Ix1OujjNuNrLrqqkDQ0WwSZwH/CRMmZC1ZtPTqGzYqyiZjCy20\nEBB8sjFqKdNayxxdU5nayLD/+7//AwIr5a+995VdIC0BJeKiBF6/WsrgVruG2iAstiebel/9+Mc/\nBuD4448HQqEBr/XMmTOz7/i/uN90I5GYOSGhj6GhzJxv7XWHNdXR3soTJkwAAvv88Y9/BEJbD4D/\n+Z//AYIF2Nhfy7Y0EtXu6nE0kIwiyzofWVabgcUJzj///CzSa6eddgJCCqSfUc9WV7bkrpbZONG/\n0vlVOscYWn+Nn3eNzXiySV6+r9vr4/WKCxtUoxOXQzVr2L9//8xabxngH/3oR0DQ/b1XjULT66DH\nBUJb4biHeDN84omZExL6GBrqZ25ra8t2XHUeo5rUg//6178CwT9nS8xjjjkG6GzB7kpUEwEWF2HT\nannOOecAIVbXhulm0bS1tWVZU0aCyQgm7GvRVYdT/5bRGx35Vg4yUuwbvuSSS4DOLDtw4MDs+pjE\nbwE/Wa/YtTZSzlY9gwYNynT1SlCuKMHMmTOzzxhpqP/cqLN77rkHCHYepUjjxJdccske12YWEjMn\nJPQadHnWlJbZF198EQg7qfpxJVkyjUQl+pYW1xkzZhSNbPP9ww8/HAg+THUqfZS33357Zh/w9y9+\n8QsglOdRz5R51Vnj3Nh8FIvbboTOLCxaJ0MbEWUVFcfw6quvZuuprhyPT+lCW8MHH3xQ9vz6e7VG\ni2rtHuXY22KMWuCVMrXijxgxoiFx/DHijDdRqc7cY7pAdhfyL1S/fv1y0HmR8xe/1kX0e9/61rey\nIIWuKCnTiIe53Jx9QHW5xQEi+TA0tBEBP6JRKZB2SrGAgkFKcemjrhaxkwEsIaGvIZfLVfwD5Jr9\nc/vttzf9HPk/XT2/TTfdNPu7X79+uf9IA10yv66a44ABA3r0Gra0tOT+w+AdXrsegwcPzg0ePDg3\nxxxz5OaYY47ckCFDckOGDMk+P2PGjOw78bFq+Sl3jEqfz8TMCQm9BElnLqBvNcO40UiUC+GEMIe2\ntraGGcCqOX9XotFlg+KQUoOWdA02674oZphLOnNCQh9DYuY6d3UTRRoRaB9LBI3oytBI11R3wesQ\nd7sQzepo0VMktMTMCQl9DFUxc0JCQs9FYuaEhF6C9DAnJPQSVJU19U00npRDs7ohNBPGSFvtohSK\nGcCKGe769evXY1xO5VDI/dbMNewul1yKza4Q9T7M+iBN3O9pqNSa3VMst7Xgm7ghV2NtT9bshIQ+\nhi5vT/NNRL54FUcH1dpKpBBidqyFLZtZuKAan3r82bgYfU9EVxZ9aEbmVWLmhIRegqYV9Pum4Juo\nb1WD7ogAyy+aVymuu+46AH76059Wfb561/DGG28EQqOGZqBYYYVKkHTmhIQ+hi63Zqtr7rzzzkAo\nOfPoo48C7cXsttpqKwB23XVXIDSXawYSM1cPC9tbgNDCg6effjoAe+21V9bAwPVuppW8WWto+yBL\nHReCVUm0BWjniBs11BMr3uNcUxoX6ukfbD0t6x0Xq4llJdBK6kt39cM8aNCg7Bo4fqtf7rHHHkCo\nUKohRmNS3jiz3+VujmY8zPfeey8A6623Xof3NRROmDCBvfbaCwi1z6xW6pzs/GFnExH3f+rXr19Z\nkb3Ra+i9aqVVRX+NeGeddRYHH3wwEKqO5veTBhg8eDAAv/zlL4HQ1dL5e46BAweWfSaSmJ2Q0MfQ\ndNeULLLyyitX9PnFFluMN954o+D/rCet+GMkjknjohJGLtXruBpYdVKGtFPiXXfdBXTcgQHefffd\njH2EXR9j2BWjWCXQddZZpxOzNRJx3zBroNvR0rnHGDlyZObC0+AjY9np0oJ+VsJ0bXVlWVyvlCvL\n/t2NhtKEjGwtb8d2yCGHMHToUCB0JRFKWd6bN9xwAxCqj1pr3MqmdgNpBBIzJyT0EjSUmfN73wp3\nqHK6uQw+ePDgzHji7izULWTe++67D2hnqGohQ9RqmIk7d1gD286IdnJwB959992Bdp0wDgqJ4f83\n22wzIBic4l1co2E9KGSYiYsBWCf77LPPBoK0IdvYd2ncuHFAe9mduCumr2XkBRdcEAhr7DFlP/t1\nb7DBBuy5554Fx57f01sUqx9eCnEHygsuuAAIHR633HJLIHQnqeSe0X4g7GW97LLLAsHuUOgeqNVY\nlpg5IaGXoOHW7Jh13GVkVXfgYudtbW3N+lCpb9jTWajvqmfVg2osoUceeSRnnHEGEBj5/PPPB0Ln\nxkZC6UHG+PDDD4t+1uus5Vtds1pr9uDBg7O10aK81lprATB+/HggsN4GG2wAhG6VSiH33HNPNh5/\nn3LKKQC89NJLQOde29o9llxySaA6VqpmDUtlheklMWlGy7OSkffhxIkTsyAQpRXZ3GvjvB955BEg\nBKZce+21QJj3gAEDyoaPJmt2QkIfQ8Ot2XHPIC2Op512GlBe32hra8vagsSMLO6///56h1kTfv/7\n32d/qxPl95WGsKubGinWXHNNoL27oXpjsWuhdVv9T8YoxcwyWbWJDLGOOWnSJF599dUOY7YflIxm\n7yvH5Tzsnpg/Hq+TnS61DHufuMa77bZbh+81KukhTviYNWtW5i2xH5beBa+F19nXxi0YF7Dwwgtn\nc7Z3mogt/Ouvvz4QpKvYp9zIpI7EzAkJvQQ9sjiB+oS+vBgbbbQREHSZekIFq9G32traMqbRsqle\n746rnitk2VGjRgHtzdX0vdporZhVW2yyySZAsJBXg3oiwMr1UI6lgPzPeZ3effddIKyluqRzMYpM\nq7bHiFNNS6HREWDO+4knngBgueWWA0IXyMsuuyyTQmL92/EqWdjV9Gc/+xkQvB35PvxylUuSzpyQ\n0MfQ5cUJFl54YQDefvttIOzyWjOPOuqooowc+3bdvbsKv/jFLzLdMo69Vc+ScdQnb731ViCw8Jtv\nvpnV8NL36GeM/ZWd1FWN/zW6qNkoxshG8f39738HgoVWC//DDz8MtEd9yUDqkDKRr2X1hRZaCIB1\n110XCL707kilVXc2Ki2WmIwIGzNmTKEeykBgZDFixAigc1vYZrSHTcyckNBL0O06s+dX/9V3mQ93\nLxnZ1zJZneevSt8yxlprtTHHvq+V9swzzwTg2GOPBYIunZ/p5NyNaBs2bBgQmNjdfI011gAq0x9L\nze8/5694DdV7ZSgtw/qdTVXde++9gY5W34kTJ3aYg8UH9t133w7va1EWSmyee8aMGWUjohqlMys1\nyMxxBKKYMWNGNr7Yn+6aKnHqqzeuXQnt+uuvB9qj2Mo9g0lnTkjoY+hyZlZHeueddzq8bwJ4obIq\nsp56ijunems9qHdX19Jp/LKRQCeeeCIQGGbHHXcE4LjjjsveU0eTcfVR63M1siq+VoVQaTvQauYY\n+6CVLpQktthiCyBEhp177rlAe5STmW3GpC+99NJAZ9+0dgN1Zde4mmKGta6hNhfnp1U51pUdg/+f\nOXNm9l2lKT0wRoSZNyAjn3feeUBYJ+/dzz//vGHM3O1idnzDzJgxg9VWWw0IN7OirAYgHe2KdV6w\nF198serz51+ogQMH5vKPXwouuCGl11xzDQAbb7xxh//7cLmJPf/88502IUVSkw/im6mRVSoasYaK\nkCbEqFIceeSRHf4PwXXnRmCQiPedCQcGV2hAqiZhot4NWbeha3TTTTcBYbN1Pdxwttlmm8xIq1pl\neKcb9e233w4EUV310UAcUycPOOCAJGYnJCR0RLczszjhhBMA+PWvf529Z9igKY4m/OuwV8QxBa+W\nxIv8XW/IkCE5CEaKSuCu7Q683377AfDzn/8cCHWxLrzwQqA94MCSOjFiw9iKK64IwAsvvNDh/WrQ\nDGYuFuQis2nEgqAiGYK7+uqrA6EElOxnCK/uL41tsn8p1MrMsSiv6KxkYfhmNdf9qaeeAsiShZyH\nkoYqldJYIXej18BjJWZOSOhj6DHMXAprr702EJLx//jHPwJhBx0zZgxQWxBJo9wausl0Rcg0Sy21\nVKfPrrTSSkCwCcSQoZU8SiVYiGIGo+6om10IMqwBM0pZMpNN8CxmoCG0kvJOta6h51DfjVFLoYO8\nMQGhYIOGPqVMA1AOPPDApDMnJCR0RI9j5kKlh2LE5WoMhzSIoRo0Okjf9DoZxRKsteCAAw4Agruj\nFjRTZy5VYCK2vMcsZ5qlQSNa7Oebbz4g6Nrvv/9+VeWEy80v//6K+1/V4zUQjjs+ppKaYatKcNOn\nT6+qlHApJGZOSOglqIuZC3UtrLdzQf73PX6cqK4l1EQEP2egQjEdqMj5GsrMlg8yiMDiDPnXyNDV\nDTfcsMP/9EXqm1XyqAfxrt6vX78cFGefkSNHZn59xxVbYoW+Y6UQfayLLLJI5od9/PHHOxzDwAut\nuTKxa2sRi//+7/+uaY6VlA2ylI8Snvq6hfprQczq3qNxSqx+9dGjR1d87MTMCQl9DA3RmUvpGpXq\nIUbMfPTRR1nInz7JOODdMRv+qFXYKKJq0Oz2NFrYTRe0bGs+4mKHMsbFF18MtIeA1opKdWaZ9OOP\nP878+479+OOPB0JvKT8rE2tttwHAuHHjMj1QZtZKbQSY4a/qkjKz6ZXVsGQ1a9ja2prdP/pxtbAr\nLVjWqRJYmNCwVUNdjUqM4bX13q0EiZkTEvoYmm7Nlplji92DDz4IBB+ynzv//POzplzqaMYyFyuz\n4y7n5wqVrylWmqXQrt4Iq2ZsTyh1TC2bMrN6lhFI5coKlUIt1mwZWXY5+eSTgRCZdPXVVwMwduxY\nIKytzLbuuutm0lRcBNBSu7F1+9BDDwWC5b6awvbVSldeZ1NNLUz/7LPPAiHl1DE899xzQIir/vzz\nz7P7yqg3Sy7rT47h9bCwYDVIzJyQ0MfQdGa+8sorgcAy+++/P9CZoWSuyZMnZ4n/WnPjCKi4bJDf\n1QobJ7yXQnf2Z45LJomzzjoLIJNQ8vVZKG5dLoRamDn2IugT1oducQIlCBvcGY++9dZbZ+WTiklG\npggax23aZy1SUTVruOaaa3LMMccAcNBBBwHw2muv+d0On5VN33rrLSB4T44//vjsGEpVsefBa6Ft\nQNavBYmZExL6GJrOzO+99x4QyuOqM9UCx1qsCXmNx6yLmeMoIiOAZE2ts/qUDzzwwKwFi61DZSPj\nlW2I5m8t/eqTFhHs379/Jz0yZsJ6dGbncMUVVwBwxBFHAMHabgEGrd0il8tl59evqmfiJz/5CRAK\n3alryopKK/rc77jjjqLjzMsZr2oN49ZJ6vrFLNDV4LHHHgOCHq6toB4kZk5I6GNoCDNbxid/F4qt\nuTKG0TdWEyllqfV/Ht+cZ/2vWrGrKZgeo9E6s/q+0WjquVrvS8VqyxDq0FYeUWf2+saRYgBXXXUV\nADvvvHOHY8a7+myzzZaDzpbhQt+3aors6tz0w2633XZAewliCGs8adKkTEIxwks93ywyJTR97HFp\nnkIW7Eoyw4qtodLN5ptvnjGyrYXMTrPYoKWgKkF+AzgI666V2zVtVKOGUuhxiRY77LBDh5u02Wi2\nASy+vuPGjcvcFxq63OB8aBTZvUF8iLwxqjx/01Mg7Uph36WLL76402bhw6lhywezXDeHUvChnDVr\nVlPXUBVBF92XX36Z1XSTQMqFvtaDJGYnJPQx9DhmrgfVVHQUXe2ayuVymdhsMH5+36H814ZP/u53\nvyt4rIEDB3bqrFDgfN1anKBaFSiuxFoJutO92BVIzJyQ0MfQq5i5FjR6V4+ZqJS0UIskUS2KMXMt\nJXG6Yry1oNAaGtprsFIl0CCmsayZqLUueCkkZk5I6CVIzNzH9K1mzLFYB4h8xAUmGolmr2Etenwj\nkZg5IaGPoSpmTkhI6LlIzJyQ0EuQHuaEhF6C9DAnJPQSpIc5IaGXID3MCQm9BOlhTkjoJUgPc0JC\nL0F6mBMSegnSw5yQ0EuQHuaEhF6C/w9JRysKUJjbOAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19704ed50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1500, D: 1.295, G:0.7588\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n4F5mB4cWAvcyOzi0ELiX2cGhheD/ATs68lSG1sm/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff18dcbffd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1750, D: 1.344, G:0.7526\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n6zayqXMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff196e0af10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 2000, D: 1.31, G:0.7399\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nlzkhYZAgvcwJCYME/w+lkPNuuwUL9QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff196ef7a50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 2250, D: 1.353, G:0.7564\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197258090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 2500, D: 1.362, G:0.7879\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nG0aDYC+zYTQI9jIbRoPw/w1nchRbyTKzAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197296b50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 2750, D: 1.381, G:0.751\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztnXW8FOX+x9/nEGICKjZgi10YCF5FvHjtzmsXYnd3YgfW\nta/djfnzZWBhoWIXNrYoKqLA/v449zPP7LM7uzO7M7uH3e/79eJ1OGdnZ56p5/t8uyWXy2EYxrRP\na70HYBhGOtjLbBgNgr3MhtEg2MtsGA2CvcyG0SDYy2wYDYK9zIbRINjLbBgNgr3MhtEgdEyycUtL\nS8OFi+VyuRb9v9HPDxr/HKPOr7XVya2pU6fG2m9LS4v2X/TvxT7TcZIcIyoKs3PnzgBMmjSppegG\nHoleZsNo73Tq1AmADh06APDnn38C7qUr9uJo2ylTpgD5L374O1Evd5iol9j/bpx9TZ48OfKzYtgy\n2zAahJYkiRbNukRrz8wyyywA/Prrr0U/t2V28Pfw9kX340vLbt26ATB+/PiS+yu1zzh07Ni2QI6S\nxP49jMIks2E0CKYzV4iv+9SLKInc7Mw444wA/P7774DTi4tJv9lnnx2AH374Ie/vf/31F+DusXRp\n6dYQXyL7enmYKImc9NkyyWwYDULNdGZZGf/++++8v3/33XcAzDvvvACsuOKK3HHHHQBcd911ALz/\n/vsA3HjjjZUePpJpXWcuRy10ZumU0jH//vvvQA/0+e233wCYeeaZUzt+sXsoSSjrcjGpGmVhFr40\n1zM8depUevbsCcAee+wBQK9evQAYMmQI4KzocV1Ucc+vFDV7mXWhpptuOsBdwK+++gqA2Wabrew+\ndEP03fnnnx+ATz/9NG+7L774AiC44KWYFl/m5557DoD+/fuX3TaLl1nXf5111gHg0UcfTbyPxRZb\nDIBFF10UgAcffLCa8QTn2LFjxxwULmejhEkx/CVxly5dtG+gTbjIB9y9e3cAJk2aBLjz0rOqCW7M\nmDGAew8GDBgAwDPPPBMcN2pZPXXqVDOAGUYzUTfX1EwzzQTAhAkTIreRAWL99dcH4J577gGyW6JF\nzepZo6XZ5ZdfDjjjzR9//AHA2LFjAbdEXXrppYE2CRnlIgktITNbZid5dnSfZ5hhBsBJLj9Ao8Jx\nFKyu/FVcGrXu9Mwut9xyHH300YC7R1dffTUAr732GuDOV/dBhjh/ad/a2lowRj3f2oe5pgyjyai5\nZL722msB2GWXXfL+rnFcdtllDB06tNw4qh1G+Lg115nLXfMVV1wRgOeffx6Au+++G4Btt90WcCuW\nzp07B9I86pqlIZl9aRLlZpGxZ7311uPhhx8G4Pjjjwfg5JNPLrrPNCh1D6Ury4gVXs107doVKAwK\n8cfmB3Ustthiga5/xhlnAM6A++abbwKw5ppr5u1L1843iHXt2pWJEycCha4wYTqzYTQZ7Sac85VX\nXgGgb9++nHLKKQA88MADAPTo0QOAESNGpH7cpJLZd3UkOE7ZbSTpJPkGDhwIwJNPPhn5nXISrl7h\nnH7QRpYkkcwtLS0Vu4v0HHbs2DHQa/fbbz8AvvnmGwBuu+02AD7//HPAWevfeuutvH2F7SKyiP/8\n8886n8jzK4VJZsNoEOoWzhmV99nS0sJxxx1X9DsKJtlyyy0zGVOcEM24ElnnFRU8UQz5JH/88UfA\nSeb2iq87K4Zg0qRJgZXXR/5WWeTTJjwGKPQrh3Xmcqsl/94tssgiAHzyySeceeaZgIuP6N27NwCv\nv/46AD/99BMAn332GeCeKa0UwtZtheRK7/7666+B5AEnJpkNo0Gom2TWrKMZq2/fvgC88MIL9OvX\nD3DRYcceeywAW221VaZjSsPC6s/2xXzWsgVsuOGGed+R1Jd0GT58eN7nGl+9kjt8iTZ48GDA+Vjn\nmWceoE0/XXjhhYE2KQbw0UcfAbDgggtmOkZJ5FL417ucBJT01flfdtllPPLIIwCcfvrpAHz77bcA\nfP/994CTzP69ksU6PBZFkyVZxRXDJLNhNAh1s2aPGjUKIJjBZ5111jjHT+vwAUms2U888QSDBg3K\n+9vbb78NwBJLLBHreC0tLcw999wAjBs3Lu8z+ZFlEZW+5+vpSa5De4kAEwcffDAAd911F+Di6KuJ\n0AqfY2tra67a/en6Tj/99IArAHHiiScCbWNeffXVARcTcM011wBwzDHHAMlL/oSP6yeFmDXbMJqM\nmktm+dQUdxoni+Wll14CYJVVVqn28AVUGwFW7vrp819++QVw51/JvoSfklfm+JllTaVBSnaKyHsY\nVXig2Bh0XrJZ6DorJlu2nO7du7PeeusBcN999wHOj/zee+9VfB5RKZkWAWYYTUbNrdmKcrn99tsB\n2H777YHShQeU+3nllVcCLq5bM2itspyKZSlJ55e11kdjXHLJJQE45ZRTCvzocVYn4PJq41hss0TH\n17kpn1z55UnIuvySfPaitbW1wHrtrzR8W4VWQGF7yXLLLQc4SayMvmrwJXPSFVDdXFO+m+mmm26K\n3FYX1w/014Sw+eabZzHEAoo9cAr0iEJjf/HFFwFYaqmlYt8kbaciC/V+iYUMeG+88QYAp556KgBP\nP/00AB9//HEw9jnnnBNw4Y4LLbRQsE0YqSFKfkgL35gUJxDD30Zjk4uqf//+zDfffACsuuqqgEvt\n9FMf49zr0HK67LalsGW2YTQI00R1Ti1zlCqm3w855JC6jUm8+uqrgJMACgDwOylsvfXWgDOmxEHu\nDwXPtBekKilYRD+LIQNUuSIKcv9IslVbgEL7lUROIin9feiejRw5EmiTxl9++SXgSidpBabz0O96\nZqPo1KlTbDWrHCaZDaNBaDcpkEm44YYbANh1112BZPqQT7WuKQXHR0lPGUoUgH/rrbcGSQZRgSaS\nCNLDopIW4tBeO1qoqIJKJgnZIKSnxiFJ47g4z4hf2VNpjAp06tq1axC+qbBNraI0bn233PGKGeRC\n56J9mGvKMJqJVHXmAw44gAsvvDDNXRZF7qx///vfQGXphmlRTp+VRNYs++KLLwb6s49vra5GImeJ\n3DCbbrppxfvQdfFRCZ9qXVVR5XpmnHHG4DpHhVxKMuunnjPtc9KkSUEY6ssvvwy4tNyrrroq1vjC\n0j/KnpDUNWWS2TAahGlKZ/bTJsUCCywAFBbDj0MSnblz584FKWxxUTrjvvvuG/xNs/PGG28MpBN4\n4JOmziz9X0XrqvGLRj138gIoySHmviI7WlQSUCSPhGwWyy67LACHHnoo0Fas7/rrrwfg2WefBVzC\njX5GFfArVhzRH2OR4BHTmQ2jmaibZJavslTigU+5vrqVkFWp3VJRPUkSJaolTckctTJKcv3LRTvp\n83A54XLEaWTgF80rhdJx9VORXwrdHD16dOBnVqLFueeeW/R4Kgnkj0eRbhMmTCjwiZc6v1KYZDaM\nBqHm5l/NtCqGXwolVCjx26ce1mslE6hQm79aUFdLlWUtRi0kclwqiSGuBMVmK1bbxz9+HIlcjCjp\nVkoiS7+Wj1sF+1UOd/fddwdc7HmPHj3YbbfdAGc/SHI8yI/h9kssV5o4ZJLZMBqEzHRmRdwodvWh\nhx4qub10qIceeogNNtgg7njiDieSUjqzX/C+VLRO3OtY62J8aejMxXobF6PSBgFhKrk+pe6hXwSx\n2P3TZ1o1qPSP0lrXXnttAP7xj38Abf5/NSbYe++98/ar5n6inMW/paWlrC3IIsAMo8nIXDJLP5TP\nTrGslaC413I5xEmo1JodlZXjI6usEvlrTS3LBiUpNKCGBnvuuSdQ2LxNNgeVri0znoKCfuXGWgzp\n6WqV1KtXL8CV0VUp4YkTJwZFF9VKSc+BPBWhdqz+WAFnzY4Tg27WbMNoMjL3M8tX55dvEUsttRSQ\n31jLb/aVJeFZr1+/fjmAp556CnC5qeGoL9/6+/777wMus8anXgXrRS2zptR6NhyzrfPPspFcnNVV\nEkuxvCSqJnL44YcDBBbsbbbZJtifYrRVfUXF8bWyUOx+OV9yKeJK5mkqnDML4jwIc801F+DcK//b\nFig0cEidKJeUXivaawpkmpS6h/5LHJ5c4z77KrCgSX3ixIlB+aNqqnH6SDX1Ey1smW0YTYZJ5goN\nYH5wiIra6Xoef/zx6Q2yCppVMqvskFZIYZUtSaGCuEg1rKQEULnxmGQ2jCZjmijo116YYYYZgiAY\n9eNdaaWVABfqV2+Dl9GGXEN+d4pwkEa5UFZJTAUxrbHGGgCcdtppBR1ZfGOtjGjljLjFUiArxSSz\nYTQIpjNnlAJZ5Dg6RlaHiDpuU+rMlZTWFb4Oq9/jFKsvF5pZ7HPfFavSvqHAE9OZDaOZSCSZDcNo\nv5hkNowGwV5mw2gQErmm4hhPsnDIZ0nYuDDLLLPkwBkeklCNwSVL4hrA4ow/yTmqumYtwlprZcSs\nFxabHZO0HwT1UFbJ2CQkbUcz99xzB+l5caOHVPDOLwUb1y8aJs0JrJpEjLTvYXubmM2abRhNhknm\nGLN6kplaPkNtm3UapyKcohqxJ/UzlyqN5KMUUZWTjdofuOwlRUxFZQgVu9blVg22zG7DJLNhNAiZ\nxWa3N72jGpKcQ1qNs8NEJda3trYGEjlpmdao+1NMKkdJxnC8c/gnOAOY9H9dF+1L41SpnptuugmA\nLbbYouD4tShSUYy+ffsCroxQtaVws8Yks2E0CKYzJ9C3WlpaCsrOFmsEVurzUui7/fr1A1xlE5V8\nFUncf2m6pkSU5VlF6n7//XcWXHBBwJVaVnM8tUeV1V/WeFn/Varn66+/BtokeblmffXQmffaay8A\n7rrrLgA22mgjAB5++GEAxo0bp7FVfay4OvM0mQKpmsUDBw6s6XFzuVzBzSlXl7nYzVTivB7gG2+8\nEYCjjz4agNdeew1wS1S9vEq3HDVqVPD3tPz54Ze53Ivtv8RaUmsC23vvvdlnn30AVwNOE9V///tf\nAHbeeWeAoPzOBx98AMAPP/wAwIABAwB45plnqjmtgGrUPv+788wzT1DTThPbaqutBrgaYHvssQfg\nXuoHHnig0qHHxpbZhtEgTFOSWdFEcv9o+an+TzKmSFptsMEGPPjgg3n7OP/88wE46KCDUhmTZmtJ\nopdeeglw9cFV9/lf//oX0CaFn3/+eQBWWWUVAD755BMArrrqKgCGDh0KuMqPIlzBNHzsMOUkkJ+C\nWayPcFLppfuiwne33nprUOhOdaUlmVVuSUtnnbvQakUSeaaZZgpWAhqXKqFKmsehmuWu/92vv/46\n+Jsk7zvvvAPAmDFjAFhkkUUAV5U2ycpAq5brrrsu0ThNMhtGg1B3ySxpqpn6uOOOC7rwRXHxxRcD\nsO+++wJutpP7Q1IgXBpXJJHIxWZTda/caaedADjhhBMAGDRoEACLLbYY4HS/4447Lm9fU6dODXoW\nicUXXxxwBqSLLroIgE022QRwgSGHHnpo3j6L6cvlZn7/c99VVI1OqdVIa2trIJEkaaVbSuJKl9Y9\nigp6+eOPPwruQxKJnAW9e/cODHhalfjPoDpV6FmU3SOO6zKpRBYmmQ2jQUhdMsftoeOHIYYlgh/a\n55dvUb9c4X8uqViqR3IcfCk1//zz8+WXXwJuRSFdWceWlBXqgqDZtlSHxO7duwOu66CsxDvssAMA\nJ554YkXnUQo/IKNLly6Jk0R0nXRPp59++kDSq+PHIYccArguidKvV1hhBaDQaq1z//PPP4NtJe3r\nlZGnXlMHH3xwsCLT+D/++GPASWqN8YILLgBg//33z3x8JpkNo0FIFDSy1lpr5cD5eatBx1XQgHrj\njh49muWXX77od+R3VapgFJLoYT+sr5uHxhGYd3fdddccOL3YJ7y/ddddF3B9p2XFlE7+6quvAvDc\nc88BsMQSSxTsT9dAUnvHHXcEKJBqstafccYZedvLkloKP+Bg6aWXzkGhZTxMUp+stpfk+vnnnznv\nvPMAdz10/VWsTucoS7Xf11jHnn766YN7VqRtS8E5durUKQfZhICGc7TVskgrUCWdaKU577zz5n2u\nFV0lWKKFYTQZNQ/nLHe8iRMn5s3wxfj0008BN1PONttsACy88MIAfPbZZwXfkSRVuF1oPAW9fUv5\naKXXDh48GHDRW7LkKhLo888/B5wvfM011wTarJkKVVxxxRUBV1Bf0lz+5lVXXRVwdghJ+TfffBNo\n621cTn+sRandOeaYA3Dj3W677dh1110BJ621qjrqqKMA2G+//QAXvllKcsnirp+S1Dr3WoVzyjLd\noUOHYAyXX3454LwZZ511FgA333wz4CR1NSsFk8yG0WTUTDKrrpZ0Jh/pya+//nrQ61Y6oXo4Sy8V\nJ510EgBnn302UBgz3Llz51SD9MeMGRPovn6/XcUSS7pKaiyzzDKAk6alJKks3epzLF1Z+pmug/TL\nyZMnB6sIjUNSUpFWSSVzuH1LOeQ7lkX/iCOOCH6/5557AGfh1rnJ3qHVSRqpsrWSzOGxKtFiyJAh\nAJxzzjmAu99HHnlksG21mGQ2jCYjc8msmdn3XUqSKBIo1IqjYB99+vQB4N133wVcFI0spNq3onKS\nUGpWL5bqp9juAw44AHC60HrrrQfAs88+mzem/v37A07fjYNsALomm2++OQB33HGHxgnkJ8n7El/x\n63/99VdJyZy0iGD4+EsuuSTg4tG1ClpkkUUC/VK+YenOWlXIHpKGz7hWkrlnz55Am36v+z1+/HjA\nxWbLviG7ThqYZDaMJiPz2GxZ82SxPfbYYwGn72qWVybMhRdeGERNffXVV4CTyML32VYikeMgiSx9\nb+zYsfTq1Qso9HVK4vglZZJIZKFyNbIIK4tG45B+tv/++wfWYfmgRdzyRb5EThIBpnvqx8QPGDAg\nsHdozMoQUzzBpZdeGusY7QnFkXft2jXIw9a5y2shj0qakjkudas0omWXDCFK9+vWrVukkUxLGrmH\n0iBJB8GuXbsGY/Af4BEjRgBw2GGHAS7goxLuvfdewPUFVvKGwlgVpjps2LCCKiQ+/hLNd79VYoCS\nQU7n6n93xIgRvPDCCwA89thjACywwAKAM5Y98cQTQGV1sn1q7Zracccd6datG+DCUOVaU8qrrwJW\ngy2zDaPJqFsKpMI4hWpGFXMlqZyOQgRrhS+1Pv3000DiqE6XDGA6H0nkSiSeXG8yLCloX2GeChlU\ngMqZZ54ZVLOMexx/u4Qrs7zfpQ4pZHH48OFAm1okw5aWo8cffzwAxxxzDOBWNiqBpBVPe25rpLFd\ne+21gfqw6aabAm6Foee3VC3xrDDJbBgNQs11Zl9iSSJLh1KgRBi/s3yaxNG3FEY4++yzBwEdMtjJ\njXTLLbcA8OKLLwJw//33Ay71T+GLAFdeeSXgiisonU6BBqHx+GMFnHusZ8+e7LnnnoCTbEIukvHj\nx1ddnVOfSQ+UG0aGR9/t9PbbbwchqWussQYAW2+9NQCXXXYZ4IKEbr/9dsCFsPo6ZqkgllCKbE2D\nRuaYY44gKEcpkAoWygLTmQ2jyaibNVuuKelSpVDK3y677JLW4QOSWEI7dOgQhJoqkUK6koJfZF3W\nLK5EAgWZXHnllcHqY+TIkYCT7r4k9gklFgBtKwa5eqSzS5dTwMkMM8yQOJyznL6vskd33nkn4AoN\nqCjEuHHjAol74IEHAi7lUimj+o4kslyYuq469gwzzBC4z7RC8/tVTZkyJVPJ7N+XOeaYI7jeSvbR\n+LPQ+U0yG0aTUXNrtsI7VZTO93eCs47Kl9ee0HhltVSZIFmeP/zwQ4AguEQ64Lbbbgu0lZyRZPYD\nTPS7/Jl+OSShsEIo9AroOwpFTbPErIr3qzuF0km32WYbwIV1Tp06NQhrlR598MEH5+1D/Zvkn5X0\n9aVgOKjFv161snz7z+h3330XnIfuu55VeRrqgUlmw2gQai6ZpUtpVpUUEo899ljQn6jWRPVQCiMd\nUNL16aefBtx5KClEs7kksxL3w5JHEld6tqKk9F19Liu+khMkjZOkK0ah8Sjh4vfffy+4J7pX+inf\nqvTy66+/HnCrrTXWWIPNNtsMcCmvK6+8MuAkrVIHfXQ+8rV/8803dS/kJ6u97sMyyywTeC2ELP31\nxCSzYTQI7a5sUKdOnWrajzdsKfziiy9y4PRdnz59+gTJD4qfVjJIVGC9/Msq3D///PMH0lqzuSK7\nFAEmn7GizCSJJZlVbiiOb9O3hHbt2jUH0RFKnTt3DmLfJRF1PyS9VSpH0lNJFDfccAPQFjuvssBj\nx44FXMyyVht+UYU4RFnZ047NVsFKFYNQTEFYH5bNRPEFSobJArNmG0aTUZVkTpJ4X+44SuUbNmxY\n7PGkQZxZXRb4IUOGBK1jhKyakjySwJLIisSSdNtwww1ZdtllgcJCB8ooUoqnJEFaJXUg+hx9XzE4\nG4IsttJ7VSJJKwxJV53zXXfdxXLLLQfAlltumXccSTTfHlAJaUWAaT/nnnsu4Owi5fz+4O5vlrHY\nJpkNo8nIXGfWbO1LNB+/gVlalItmSqJvderUKdBjo5qA++V+Fa2kcXTp0iUokK52poqk2m677YDy\nObCKGJNOW4py+cyl0D3xY7O1elK73Ndffx0gyCg777zzgqbq8gzou9K7y/ljw1IxRjO8iiSzrNSy\nESin3rfm6x7qekyYMCGI+Ev7eS2GSWbDaDKqksyaqaRTlvLPKjtKDbaEdCbNkrWY6cKEZ735558/\nB856XExCahZXlJofpaXfw61MwrS2trL00ksDLvvIL9DnXwP5ahVNFfaHJ1l5/O9YFSvgfiSa7pns\nBsqQuu+++4LrELd8URL8c07Lmq0V00orrZT3u+wJKpesMsK1Iq5kznyZLbeLDAUK39ODoZcjbHip\nJWm7NZTiN3To0Mhtol5A/V1lgZRmp2W1alAp4aAUxYxD//t76okIupdho1Ya9bDjUquyQfXCltmG\n0WRkJpnVa+fMM88E4I033kg4tNpQ6ayuFUepet9xkRTT6mXgwIFAZcs5v1BiuWW2L0HTCBEthq+G\npIlJ5jZMMhtGg5CZZFZZWCWflyMq3S9rkszqM888cyCJQ98B4JJLLgFg7733zvvc7zW11FJLBS4p\nJR2UO/dS+qeMjn5wikhqAJtxxhkLgkHKofDS1157DWhz7fjJGXL3VGLgLCfVs5bMCklVbfIrrrii\noFBClphkNowmo25lg3yqmbmrIetZXVbt008/HWgrLCAXk5Brx5f65SRSnMCKKMmcprXZ7/Tou+Oq\nRWPVM6LrpcQT05nbMMlsGA1CIslsGEb7xSSzYTQI9jIbRoOQqAZYIxgXFOyh/NNmM540+jmmeX61\ndD+Vot3EZpejmBU7KkkhC+xlnvZJ6x7WMp48CWbNNowmo+6SOWuUlqdWMPLZ1rrpWL0wyVw5WcaT\nJ9m3SWbDaDIyk8wyMMnglAYqPVOsIXulmM487ZPVPUxTh1YhChVrTIJJZsNoMtq1zuxbuk8++WTA\nNSU/7LDDABg+fDjg9A+VsylXGA9MMjcCad1DPW8qh6U2rfUmrmTOvNdUuRfLTzJIMrmo04BqNKvn\ns7opvPbaa+EevglHXj+U1qhKln795mKdM+uJOiCqYqlqnIU577zzAJdw8sADDwCw2mqr1WKIsYiq\nwZYEqYLqhqF+00oK0b6L1SmvFltmG0aDkPoyu9JURnV5UA3mSvBrb3/77bfMOeecQJ4rKu/3aWGZ\nrY6Tqsr59ttvx/5uLZbZuu6lIqWijJd+x0vf6NShQ4eyz1J7uodJjWbrr78+I0aMKLmNGcAMo8lI\nXWeOK5Gj6mjHQWGeCvvcaqutgMLStJLK0P70zDAbbrghAPfffz/g9C11g/zggw/y/i5GjhzJ6quv\nntm4oqSMYpbVg/nWW28tu68od6KOIWOTbCjavlpbx6GHHgrAOeecU9V+yqFn7YgjjgDg4IMPjvW9\nclI5CSaZDaNBSEVnlp7c2toazLB+cTptM2rUKMAVgSulY0sCy6ordtllFwCuvPLKvH0sv/zyQDK9\nuz3oW9dffz0AO+ywQ9HPq1lNZKEzr7rqqoDrLVUMFRbcaKONALj77rsBp1/7hfOF+lzLTtDS0sJ8\n880HuAYKPkk6ec4000yBtyCO67IcejZV0PH//u//AHjooYcAZ8WuBtOZDaPJSFo2KK8YXCVIAmvm\nVh8ldTQ85JBDuPzyywE3i/tjXHvttQFXAvWjjz4C3EyrQvBxZsV6Sub77rsPcNLLR72OVNC+EqqR\nzLr+fvle+U579uxZ9Hvh58PfR9znTfEJkyZNihyHKHYPS1mV/c+SJlS0tLQEq8GXX34ZcLEO4vbb\nbwdgt912Aygo4pgEk8yG0WTULJxTes/jjz8OuNlQUVxhC7U+ixqbJNXcc8+d9/e55poLcNFkKjJf\nDEUt/fzzz3WTzFHnl6bFPQ2dWddTvmL99NE1Peigg4JoPFmRFfEkC7hWZFEkuQZJV1daCcl74B/T\n93yUekf8z7TyVP9mnbcaH1SCSWbDaDJSlcwTJ04MfL8+0jEUi6pZXCh6KGrWDxM15ueffx6A/v37\nR343q96+SZDup2vi094ks9hrr70A17bWJzxurZIUrSZJVQ4/ii8Old5DWaL1zMmvHwc9vz/99JOO\nCxQm+5SrH9alS5eyVnWTzIbRZFQVAaZYYfntoqQyuKghXyKLKEtlmHKrCKVCxtlHPYu2yW4gS6f8\ntb17967bmOKgJoBq+j5mzBgARo8eDbjmdePHj+fhhx8GnESOisCTBJNVWPuQxMsC2WQuuugiAIYM\nGZJ4H5Liugay7J911llAfSp6mmQ2jEYhl8vF/kebnzny35QpUyI/69KlS65Lly45n8mTJ+cmT56c\n69OnT65Pnz65ww47LNfS0pL7n+6TA3ITJkzITZgwoeC7Yvjw4bnhw4eXHFvUvyTnl8a/PfbYIxj3\nlClTSl6zNP4lvYdx/un+aPzVkPY5xhl7a2trrrW1NdezZ89cz549qzq2nmv/2sS9hkBuwIABuQED\nBsS+h1H/al5pRIEeWn5pWaXl9/jx44NgiS+++MI/ftF99u3bF4BXX3018XhyNTaATZ48ucDwlWXy\nRy7DFMineADWAAAQ2UlEQVQkz47CfJ999lnABf6kNI6aGzF9Q20ahQ2i8O9hFLbMNowGIfOyQUIB\nHgsssADgZvVVVlkFcAkYm266aWCq1zZ+ML5PJRK51hx11FFAtDtqWkQJIjvuuCPg3DLF7pdSA3fa\naacaja44iy66aJBSKpIWFGhpaQlKI8lw++677wLJJfPMM89c0Je7UkwyG0aDkLnOrCRzuSD0u19q\nRp//9ttvwf+jkHQbPHgwAI888kjSYQVkrW9JtwpXetT/y51nNYQKGZbUmdOoDS3XpAoBXHrppZHb\nKuFARQjSIOt7KHvOLbfcArQlwKy88spA+TTKckkira2tkQkees4nT55sOrNhNBOZ68wqDyRdQoEm\nviSIEzQiFKx/5513VjwuJcsn4YknnmDQoEGxtlXngrfeeqvgMyXKZ0ncdL4kElnBLSpOIC+CgoVk\nF9lqq6245pprgMKECv2uQBMVlKgVAwcO5Mknnyy5ja/zP/fccwB0794daHuWTzvtNKAtZbcYWvGU\ne65L3aek+rdJZsNoEDLXmaUXKh0xyqeqcYQ///777wHo0aMHADfeeCMQXV6nErLSt0oV369lUcEs\n/Mw6Jz9VVbED48eP54477gBgiy22KLoP6aG//PJLtcOp+B5GFSXQ/dHKT7YZlQbaZpttCrwyPtpH\nGk0YzM9sGE1G5jpz3KJpxaSVJHK4hEwSSlkKsyZqJm6PpX6T4ktknVM4hVASWSsyFae44IILAGc7\nSUMyJ6XcPdAzK0u0SloddNBBANx0001lbQ1apeyxxx4ADBs2LO/zcJHCtPpAm2Q2jAYhkc58/vnn\n5yBegW+/HUm540iS5XK5oNvjueeeC7jZXellhx9+eMl9yWIap4ha2jpzuTK0HTp0qOlqIQ2d2U+8\n91EZHjWDmzp1anDfZbmX9NG9LJUum5S07+Gbb74JuAZ4St+VNVu2nFLovJOsJqPKTpvObBhNRlXW\nbM06c8wxB5Cv/2g2V6TMiy++GOsYP/30U+Cj/fbbbwE3MypabJNNNgHg3nvvjT32KNKa1ZW4r4ID\nPiuttBIAr7zySqWHqIg0JLPK6yjSqxwXX3wx+++/P+CkuVrrSFd+6aWXkg4jkiT3sKWlJXKVGLbG\ngyuFrOetXm2BTTIbRpORmZ85rn9t3LhxACy00EJAm67966+/Ak7PlkSWlXHhhRcGnE7sSwwdM06G\nUlqSWasIrVJEpZb4tEhDMg8dOhQoHXMdRVTsd1ZFC6u5h9KJVcBe/uVq4tbLUWqlIEwyG0aTkUgy\nf/nllzmAXr16AcVnLGWWbLfddnnbqGiaZvcoX2WfPn147733ACetVa5VemexeOcwsoYff/zxZc8p\nqwgw6V9ZFqaLQ1zJXC67B1y8ecJm73nfkYVYjeHUKK4a4tzDSrLD4lyTNI5TjriSuWZlg1QKSMYs\n9St69NFHAfjnP/9Z8B1tqwvkVzz0xz5y5EiAkj2LfQd9tS9zJS6IWpJl2aA+ffoALjFf1/+GG27g\n2muvBZxKpAk6Cyq9h1m8eFlgy2zDaDIyk8wKClh22WWB+K6pWlOPYnC1JEvJLOS6KtXbS4Ubswjf\nbLZ7GIVJZsNoEFKVzD169Ah6SSXVQ8LuJF+XUcndqH7AcZDupl7OIutZXUYUpW1Kl6wVtZDMQn21\n1ZMqCdXor2ndQ79Di9A9lJtx5MiRrLbaaoDrXpql/m2S2TCajJoXwY+iWHGCNFD/Z7+8aui4TaVv\nNfo51vr8ws0bssIks2E0GYkks2EY7ReTzIbRINjLbBgNQqIaYFHGBQWIyEz/v22BaStUrtGNQ1Dd\nOb7zzjsALLnkktp3NUMDnMtQFVpUgTWM/yz5vzfbPYyi3Viz60WzPQhpnGOWE7UfDxCnKGOz3cMo\nbJltGA1C3STzpptuCsA999yT1i4roj3M6mmVWi2GP6t37tw5B4UZaCJOsnwUfnmntCi3EmgP9zBL\nTDIbRpNRd5253oayWs/qLS0tgSSeZZZZABcLrNa0a621Vt53qsmZ9mf16aabLgeuBHIpjjvuOABO\nOeWUop9XsqKIKidbCaESwFXdwzhZX2Fq3VzBJLNhNBl1l8xCbTw22mgjNt98c8AV8FNR+7gzZxKy\nlszF3CrSKSWd1DBAqEyN3/q1EmlQzppdLM84zdWSMo1UFnmdddYput2cc84JuMKI33zzDeDaxEJ0\nGZ96rK70TOpeqgxSFhVVpjnXVJxxZNGnqVYPwjzzzAO09RgaNWpUyW01sakMz/vvv1/xceO6pjbe\neGOgrVZ0tQa5jh078vPPPwNuKa6lbFw0wU2ZMqXurimdg37++uuvQWyFnttlllkGcC+zJmq/G0gl\n3SFtmW0YTUbmXSDjEi7ap+WU/9m0zNdffw0ULqkB+vXrB9SmtFJUVUx1b4DKJbLUgt9//z1WzfJS\nrLvuukBbocf99tsv77Os0mWj0PVQYYmwAUyGxLFjxwJwxRVXALD33nvnfdfvuZZFdwyTzIbRIGQm\nmWW8kgEkCr9bZFgqaxY7++yzATjssMNSH2et0AwdlnpHHXUUUNtih1F1qqsJ+NB3P/nkE6CtEMTi\niy9edNuozhayI6yyyioAPPnkk0Bhh5Dwd2qN9NyJEycGKy11v1C8ugxjcfuSpzq+mh/RMIxMqMqa\n7bsTqkHWzh9++KHAUijpHifQISlZW0LV2eLHH38s+GyDDTYAYMSIEWkfNiDLskGSyFptqJijSulA\ncRcTtBV/BFduR50/tA/p9v369Su7cqmVR0Ln+ffff/Pss88CztWmZ3bChAmAk+J6dku5VZOEq5bC\nJLNhNAhV6cxpSGShXGjNcOCkmYrylesxVS1phhoq9FIztDpWSqeCbCVyFB9++CEAiyyySNX7UiBI\nMYksKeNLZPH999/n/X7zzTcDsOeeewKu5Y3v2aglune33nor4M7pwQcfZOuttwZcAIsksp5fSeQ4\nhf7SCmU2yWwYDUK7iQCTVbtYMoFCDtW3OU3S0reef/55wEmc+++/H4CrrroKgLvvvhuAzTbbrCZ+\n5VCEUWo6s/b52WefAS5BZLHFFgPy/b+SqKEGfUX3qXuryKm55por73s9e/YMLMdK+FACSFqJFuVQ\nEwatRJdYYonIiLZKVnflOoaazmwYTUa7kcxqDSLdMszss88OFLcIJ2WppZYCnP6dtiVUkVQbbbRR\n2W2V3CA9epNNNgHaWqIC7LLLLoDTTSshqTV71llnLZAQ0gO1eho9ejQACyywQN52kkbTTTddIInL\nRZP94x//AODpp5/O+/tll10GwD777FMg1X3pl5U1W6sL3/4xatSoYHVVi9Rdk8yG0WS0G8lcKotk\npZVWAuCVV15J/bjVzuq+j1B6ZNIsoYixAc4CrSgjPwWwzD7yZvUll1wyB67SZlRaYRjFE7z88stA\ndAM/xVOryEIcttpqKwBuu+02wEly+WWXX375gmZ/ImudOWq1+NJLLwWRav5YrHGcYRhV026yplSQ\n4OOPP2ahhRYCCHJi05DIafqQw2gmll4p/f71118H4NFHHwVg3333Bdr8jpKGM888c8l9a7aXn126\nWzUZSZLIokiif7BKUoTXl19+CbjMLx9d0yQSWee222675f3dj5z66KOPOOmkkwA44YQT8rZVFFlW\n7LjjjkX//scff7DlllsC8MQTTwDOn1zPOvHtZpktvv/+++CF0Nh0g7MgbeOJP1Y9tDJy/fLLL6y5\n5poAPPbYY4Bb6mo5F/WS9+/fH3BusDhUEs6pl+SSSy4BCB5cHy2FtRxNgsI1lTroI/fTqaeeWnZf\nWRnAunfvDsDnn38OuHs4dOjQwIWmCUaTtep+v/nmm0A6/bhtmW0YTUa7WWYLSWWoPtXt7rvvZrPN\nNqt2SLGQu2b55ZcHnCFMUla/A7zwwgsA9OnTB3Cpg2LQoEEAPP7444C7Ds888wyQToijpIyWswrJ\nPPDAA4MVkdxrMkpp1aHkgosuugiA2WabDYjnOlxuueUAePXVV4t+riX78OHDk5xOJiiNUyshqREP\nPPAAJ598ct62GvcBBxwAuPt93XXXAbVZfptkNowGoe46s4w5MiCEExGU8uhXqYzLLLPMUjYENG19\n6+233wacYUkN0aQ7DR48OAjfK4f0yo8//hiAtddeG3CJ+3FIqjO//PLLQTEIuYuEdGSFcyoARzqz\nkg2KIf1TASlRpX/k9pLRrRR6diZPnpzqPVRwjPavQKAVV1wRaDN2yhipcNSo5nYq5Dhu3LiKx2M6\ns2E0Ge1GZy5msS5W/C4JpSRFWviSZdlllwVg++23B5w7SaGZ4ba3UehaKBFDLrpiJXTSpkePHkHR\nBCEp2atXL8AlVkiXDtsDfBRc4Ydr6rpJ19Q5x5HI+m5W6ZEa04ILLgg43VnHO+KII7j00ksBpxMv\nscQSAKywwgp5+5I0f/DBBzMZaxiTzIbRINRNMvszs/SuYjp83I6RfvH2WlgQtXqQxNX5aBZXMIkS\nB0oh/658lAqjFL4OmwX33Xcf++yzD+Cs7LK665z8rg263uGeTSpoJ70zSorq8ySxBLqvlfTeioP0\n9kMOOQRw9/Caa64B4D//+U9wzrIvKNVVKMAmSSBNtZhkNowGoe7WbJ9i44nyN0eFaGofv/76a5Cm\nFyfxu5rzkxRVATuhGbxYCKYvrSQJ/UQGfTeNXlNdunTJQbRUe/zxx1ljjTUAp6sPGTIEcAUXZMUe\nM2YM4LwNsuCPHTuW+eabr+S4vvvuu7x9V5Lmqair4cOHp2rNVnSXpKtWRNtuu62OEUjrY445BnD2\nDZU/8ssHJUmO8TFrtmE0Ge1GMpcqGyR9uj13gdQYVTYoXJgQnM/8zz//DPoyCz/CSkgHjWMBj8Kf\n1fv165eD6JJFo0ePDqK09GzILy7pIqu6ot4UZbfzzjsDzpIfRp4FRcRVE93n+3TTuoeyWSg6TU0K\ntCLReXXr1i0ofv/UU08B8NBDDwGuKL6s8tU0/RMmmQ2jyai7ZJbeKOkT1iOlC0tnnBZauvqRTqVQ\nZJdSPiW9e/fuDTj9u5oWq3EjwGR1bW1tDYogyA7gZ69Jyir6qcgxg3ulyD5J80ra30RRrGhhNfdQ\nY1SWlMYajkqENluMv7pSAYWVV14ZcPaGNDDJbBhNRt0ks/JY/aJwuVyuQL8KHT/WvmVdjeOHTFsy\nS1qpWJ/PU089xcCBAwE488wzAee/FL4ftxqSxmb/+OOPwXXXiki2Cj0r5YoqzDnnnEFMsoo0JCVJ\nGZ6076EflVYKSWDZSvTs9u3bt9phBJhkNowmo+46c2jfQP5MHNX+M01q1XSsXviz+meffZYDtyIq\ndv8VvaV8arWK2X333QG3+pDkkq4vv+/VV19dccP2Ykg/jcqAy+oeKvJN2WrKsR4/fnxQGF9VYxSf\nLj07zfOPK5nbzcucNVEJ9M32Msc5x3JLXKkvcp35obnVhNHK+KZU0jhkfQ9llA2fnwJ79FJniS2z\nDaPJaBrJHEWjSGa5T/waz2n0Z1aVzizcSpUsR+XKk2uvUe5hFCaZDaPJMMmc8ayeZaeDOFQimaMS\nWKL+HhWOGv6b+hnfcsstRY8Zp7OGCgjuv//+eX83ydyGSWbDaBCaTjIfeeSRAAwbNgxovFldxf4U\nmJKGzhyFVh0KO/3ggw8AWH311dM6BB07diyQ1kWKUDTUPSyVSFIKk8yG0SAkksyGYbRfTDIbRoNg\nL7NhNAj2MhtGg2Avs2E0CPYyG0aDYC+zYTQI9jIbRoNgL7NhNAj2MhtGg2Avs2E0CP8PqJZbeCIi\nmTAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19744ff10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 3000, D: 1.379, G:0.7309\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztnXeYFFXWh9+ZASWoIGAAZBVFEEVEWVTMroIYMCvmZRUU\n05oD5rRgQN01rIo5LyAGDICgmHNCQURAxQAoKvIhCIaZ74/xV9Vd3dVd1V3V3dN93ufhGTpV3Ur3\n3JOr6urqMAyj4VNd7AEYhhEN9jAbRplgD7NhlAn2MBtGmWAPs2GUCfYwG0aZYA+zYZQJ9jAbRplg\nD7NhlAmNwny5qqqq7MLF6urqqvT/cj8+aJjH2KVLFwBmzpyZ9vNKu4Z+VIUJ5yz3E1XuxwcN8xgb\nNaqXOb///nvazyvtGvphy2zDKBPsYTaSWGmllQq6vx133JEdd9wx43d+//13X6mcD1VVVVRVBRJ6\nDQJ7mA2jTDCdOSJ9a9111wXgiy++0LbSfq9x48b89ttvue4mNOWgM3tp1qwZAMuWLQPi15k7dOgA\nwPz58wGora1Fz00hUohNZzaMCqNkJLMkWcuWLVm0aFHk2/U7zrhm9ZqaGgCeeuopAPr16wfAL7/8\nQtOmTZO+27VrVwCmT5+e9Nso8M7q1dXVdX++H9k+4ma99dYD4JJLLgFg4MCBSZ9HdQ1XXnllwLWe\ne1dXv/76K1C/ulpnnXUAmD17NlAvrf8cS9ptZ7oPq6urk7bhpWRcU6uvvjpA1gf0wAMPBODxxx/n\n559/BmCVVVYB3IP0O9h8iOpG8C79XnvtNQC22WYb7cf3tzo3p5xyCgCnnXYaAFtssUWuw3FoKMts\nPbBSUx555BHAvS/A/4HI9xput912AMybNw9wr+HSpUsBWLFiBQAXX3wxUP8A//HHHwCMGjUKgPbt\n2wPw5ZdfAjifRzFp2jLbMCqMUBFgYZBU+eijj5Lef+mllwA49thjAXjuuecAmDRpEgAdO3Zk5MiR\nAJx00kkA3HDDDXENMxSNGjXydZFoNhd77rknQEZj1yuvvALAZpttBrizeBQSudTZd999ARg7dizg\nnqf33nsPcKVlIlFIuTXXXJPvvvsOgMmTJyeN5ZdffgHgoYceAtzVwV133QVA586dAfj+++/Za6+9\nAPjwww+TfnPppZfmPcZcMclsGGVCbDqz9JuffvoJgF122QWAKVOmAK4+rBm5cePGACxZsoSWLVsC\nMHXqVMDVo84880zAP0Y3F6I2gOm49XfMmDEA7L///s53nnjiCQD69u0LuIYX72+jCGjIRWfOZpDx\no3Xr1kC9rqljWrx4cdrvvv766wD06NEDwLGTHHPMMQCMGzcu5Tc6Hxpfgl4a6ho2b97cGSfA888/\nD0D//v0Bd0V49tlnJ31fhrEffviBadOmAbDDDjtoDIB7LaM0MJrObBgVRmySWQ72tdZaC4DTTz8d\ngGuuuQZw3Qxbb701AHvvvTdQP+suWLAAgIMOOghwpbn0Us2UUZBpVpcVU7NtPjRp0sTZ5sKFC5M+\n0+z+8ccfa0xJnyvEMpdgk0JYszt16gS412v69OmOPirpvnz5cgBuu+02AO68807AlbKvvvoq4B6r\npG4QMl3D77//HoA2bdqk/E6SdquttgJcj4R0ZHkV5F7UdamurnbuRe/KUveK3FhRYJLZMCqMyK3Z\nAwYMAKBVq1YA/Otf/wJcX6pm5FmzZiV93rZtW6B+Btf/N9lkk6Rth5mtoyAXiSy/8mqrrQbAhAkT\nANdSCqm6sFYvfsenWb5UkgI0jiuuuAKAc889F3Cl7LBhw9LqvPoMXDtIixYtADdkMuprnE4iy3r9\n5JNPAu6qQL7inXfeGXAt6vJgyIbTrl07Nt10UwDOOeccAI444gjA1flvueWWSI8jCCaZDaNMiE1n\nfvrppwE46qijgHoLILizt/4KjaO2tpZ///vfABx99NGAa/mWJLjwwgsDjzkbcQfpS1f0WqwTOfLI\nIwG47777Mm5LelmYdECvvtWiRYs6gP/7v/8LvA0va6+9NgBff/01kBp+Wl1d7WvNlY4pffWFF14A\nXGmYC7leQ+nnfvqt7tGbb74ZcO/DCy+8kHvvvReoj4uAev81wPHHHw/A3XffHeIIMmM6s2FUGLFF\ngClCxjtDy7opPVFWb+lOS5cudeKaDz/8cMCV6pdddllcww2NdDuvVOrTpw/gRrTJ9yrdqkmTJo60\nFvfffz8ADzzwQNK2vVL8zTffBKBnz545jzsfibzqqqsC8OmnnwKp45PvdaWVVnKk3pIlSwBXEuuv\nULRfMchmcd5www0BV6e+/fbbgfooL1nwdR/LJvLjjz/GMtYgmGQ2jDIhUp25W7duzuycDekjW265\nJeBmGR100EE8+OCDgKvTyCIp/eTdd98NPOZshNG3amtrU3R9ofcnTpwIwO677w6k128V4aboOC/y\ne+qceCOevNItE1GmQMoPqwipq666KulzxSUPGzYsReplSw3MBf22trY28DWsrq7OGtmmVaJsFPL/\na2VSW1vreGM23nhjwI0V6NatG+BG/vlFwIXBdGbDqDCKVpxAs6p0zAsuuACAzTff3JHI3uJyiuOV\nvy8K0klm6cEho5C0jcjGJkmoGGJJlDDFC6KMABs9ejTgRnpJ+uo6SVq9/vrr/OUvfwHcCD9FwAlF\nZq2xxhq5DschLo+EVkQbbbQRgFOQYMqUKc5nqumtayS7hyS0pHk+lExxgmwoWOCOO+4A6k+UAgu8\nD4YCMRSUH3Xidz7HJ7eFDEx+y/EgyHi26667Jr2fmMgAbrhpJqJ4mJ999lnAnXgTtp00niFDhgD1\niTBvvfWW9pf2N1I/dE1lFJRr59Zbb036fibiepj9xg7u9ZXLUWmsCo7S+HXuhg8fHnh/mYovZMKW\n2YZRJhRdMqdDBh5vYoGWmZoFgxrbMpHrrO51TcnFMnjwYAAOOeQQwC0rE4QEgw7gGshkkJH7I0yi\nST6SWYkGI0aMAPxXG0OHDgXc0j+HH364s1LxovM2fvx4wF2RXXvttYCbtCGCVDONSzJLfdAqIp3h\nTN9RySE9TwpTfvzxxwGYO3du0udhMMlsGBVGbEEj+aDZSwYVzX7SRz/55JPiDAxXevbu3Rtw9Vav\nsa579+5AMMksI5ES9oWk1FdffQW4BrFsFUdzQZL0559/diSwQhJVWEErBVUa1WutQlTMLp1UVhqh\nykXJACZUXkqGMunQhawx7kUSWec50TCqcyQjoJKDFHKs70qn1mpK11BpsFFeQ5PMhlEm5CWZcy0v\nk4nVVlvNmc1UyE9uDhXJy9YVME40k8pa69eb6fzzz8+6LUlYSTqve8srvbxjyAedQ0mWRH1Y11NW\n6pdffhlw7QJKtDjhhBMAV/9VEEldXV2K/r/PPvskvfby2Wef5X1MUaPzLKmrlciKFStSEmdkz1BB\nQqVZykbw9ttvA+6qMo7VlUlmwygTSsaaLed6dXW143iXnqWCB//9738B1w8rqZKY+B+WfC2h+YQp\n5jor67iDFE+Io2yQN41Vx/HGG28A9YEUup6y8irxPyyJ5Y3jKoKfbp/g2iwU1yCf+IwZM1LGor8K\nFlHhA31PAU/eckNh/eiZMMlsGGVC0a3ZimpSGuD+++/v6F4KH9Qs//DDDwNuapqS44XXElpMVL5V\nvtrEENSTTz450DZUekZRUVqBHHfccZGNMxf82gUpYm3RokWO5MlVIotEu0hc/bEkPaUby1ah6ESt\nEBV6WldX54xFfcO0WtI9q9RISXWFhCqtV+HLS5YsiczmZJLZMMqEoklm+eEOOOCApNcrVqxwIryk\ng8kyqCIFmhW9iRCSyLJ+L168OJIUtExoVvVGR6kMzgcffBB6m/Kny1o8aNAgwPVRlgryJ0sPVERe\nXV0d++23X9HGFRZvjLmk6KOPPgq4LZWUgjt16lTHi6G+3PJeqIWNLN8qbKjy0WeccQbg6sxRJuaY\nZDaMMqFkrNnSd9dbbz2nQL5mekUNSQ8JUwI3TO/bfI4vCn0ujlK6cRbBl79ZpYH0t66uzilFq8T+\nOInqGur8q6CkVobyESvCra6uzmlVrBWl0kKvvvpqwL1nJdVl30kXG6HUSq8NSJg12zAqjKJbs4V0\nrP79+zt+ZTXaVhyrN3rGG2WUjjgatKcjioieXIoiFAMd64knngi4PlRJnfPOOy9niaxVV5Bc7Xzx\n8xWrGKW8J8p40spwjz324JRTTgFcPXvzzTcHXB+1ygbpOHQfqiSv2sqCv0QOi0lmwygTSkZnVubQ\n7bffTteuXYHUeFf5Mb2ZNCq8lm9jtTiOT37I3XbbDaj3ZV555ZWAm6ecDzpH2o+XOHRmxZI/9thj\ngBufrhK8KnL35/7z3V1WwlzDpk2bOl4Pv7HJQi3Jrda78vevueaajoRVW5odd9wRgFNPPRUoTuO4\noj/MAwcOBHCWLZMnT3YS1ZUSqGXP9OnTo9597A9zsQn6MGsyWL58ecpNLmOP+oSpeqiCefRXYbiD\nBw8OHbiTz/I612sYNFFIQSSff/45UH/8aUJKgXhUJTOAGUaFUXTJXGwKLZkT0wMLQS7L7GzGPBko\nVRtcCfmzZ88OPK4o02fDXkPvvmXY+vbbb/MeSxyYZDaMCqNBSeY4ErpNZw6OXxfKfK5HFNe00q6h\nHyaZDaNMKJmgkSAUws1h+BNHcb1yu6b5uEnzxSSzYZQJoXRmwzBKF5PMhlEm2MNsGGVCKANYuZv9\nozy+Vq1aAfDjjz9GtcmciDOfuVQw11Q9DcrPHAdhboSampqST0/0Yg9zw8f8zIZRYTQoP3OxSSeV\nvS1lokAJ7mqRqlhipRjGEQlnxEPLli0Bt8BfnJhkNowywSRznnhLGOUjLdXSpE+fPgD89a9/BVKz\nkUwiNxwKIZGFSWbDKBMatDU7SGtXvyL1IipLaLb95LOtTNUrVHrIr9h/OVmz1cLoyCOPTHq/oVuz\ns9ldStY1la1GcC6ot+/6668PwPDhwwEYOnRo1t829BshG6X6MEuFePfddwE455xzAJz6aGHI9xqq\nc6PqtKt0kUopeSfRP/74w5lgxUMPPQS4vaSESiqppngumGvKMCqMgknm5s2bA26d4XxQLyZVhZw5\ncyaA06MqDA1dMh966KGAW+PZS6lKZqkSfkvLMK6+UupKov5g6iWubeajfplkNowKo+gGMPXA/eqr\nr4LsH3ANXiqBqo72frWjM1FMyaxEdulomr29Uimqkjp/bruoklmdPBW7LrxGv0JK5lzOr/ouqxNm\n0O/rnpXOrY6lWcZnktkwKomCSeaPPvoIgOuuuw6ASZMmAeGs2pLIXktiwvhCjyvMrF5dXR1Vadik\n1+qmKEu/Onh4uyLIFZf4epNNNgHgww8/9NtXUSWzt6ytjl2vtTqRxTjua+jz+4yf+xUyBNduozJB\n2e6Ptm3bAu4KJUh5IZPMhlFhFCyc88YbbwTcFifeMMgg+Enkf/7zn3mOLj3eEM3EWTdsG5Kdd94Z\ngOeffz7lswULFgDwzjvvAK4P1qtHLlu2DIBmzZo545JEjiPhIxval7okyv6ROAYdQ/v27YHUY8hm\n1Y4Tr0TW+NVDS214Mklb7+qpY8eOAMyaNQtIXU2p+2Mc3UlNMhtGmVAwyazGcN7ZXDO0ZuwwLFq0\nCHClfr54pZv3db9+/XjmmWeS3tt7770BGDduXNK21OpE3QKDIIks5LO89dZbAfdcidraWmeMZ511\nVuD9RIV0fEk0NfpLxzfffAOkHkMppXNuuummAPTq1Sv0b7VS073olcjyO6uXtewiUWKS2TDKhNit\n2VOnTgWge/fuSe/L37bGGmsE3pYksRK+pXf46dJBCGsJ1fnyxu/qfbX9VGGBMAkY0qtffvllwNXH\n1aBt/PjxSfuqq6vLut04rNm6ZrqGssh6pVEi+kzflWVYluJ8KIUoPvV0lt1DsQ+ydot8rfWZMMls\nGGVC7DrzL7/8kvZ9bwRQIoMGDQLgjjvuAFwpJ4kscsmwyRf5y5944gkgVdfTWMUXX3wBuBld6Wbm\nbO1NJZFlCe3UqVPSWArNwoULATj77LMB1/qbCa8/tXXr1tEPLABVVVU56+eJ10nXStlQWmF4oxC9\nUYtxYpLZMMqE2HTmnj17Aq5V1xt7LSlz8cUXA3DDDTcAyTqU9BBZvr1ods+nNnWujbqlE6ksjMYi\nPTJhmzmPzYtmd+msy5Ytc3K55cf1EofOLMmsuOK99toLgDFjxgD1ZY422GCDjNuI8rzErTNrrEF8\nw3qeTjzxRABuueWWvPdf9OIEYU5Arjz77LMA7LbbbjlvI+yNMGzYMADatGkDwKWXXgq4Yaknn3wy\nADNmzADgueeeyzoGnSu573QjLF++HICBAwcCrutHS9bVVlsta9BKlA+zjHtbb7014LoTO3fuDLgG\nymnTpvkmvay11lqAOyF477+wwTh/biPSh1kFBeROUpppEEOrjkeVX1ZfffV8h2MGMMOoNGKXzCuv\nvDLgbwjzsmzZMiewQO4fbUNEkfCdsK1Qs/obb7wBuKF+99xzD+BKz4Rtpf19y5YtneQIlcyRhMu2\n9LzvvvsAN0Bl5MiRWQ1JUUhmqUri3HPPBWDUqFGAO34FkWRKZ9W19IZB5kPUklnXoUuXLoBraEx0\nvfXr1w+ACRMmAG5IrpJmEsYGWHECwzBCEKlkrqury1oGRjp07969Abj66qsB2H777YH6JG7phqof\n7UWF+qJwTWWa1RWKee211wL1VSF1vmTA84ZrZpOuEydOpG/fvknvNWnSBHBXL9OnTwfcQnN+NGrU\nyDGAyVjoJQ4DmDcEUyWhNAaNP91v4iBuA5iui8I8VfjPZyxp39d9IltBGEwyG0aFkZdkjiLtTlbP\ndu3aAfUB+dn067jdGpmOK9v5ylD7OOU96ZwDBgwAXNeTdFC5v4Luw2e/GSWzglq8wS65kO4YR4wY\nAcSbCFIK4ZxCurEs+7qGDzzwAJBa8zsIJpkNo8IoekG/hG07//fzTcvPF6XvOuysrjH4hedlC80M\ngrbtl7iglcuTTz7pSHU/Clk2SPfSBx984KT6FaLoQJBrmIv/OheUWCFPjFCa6Pz580OPwySzYVQY\nJdMFUrO6N5kikTijyYKSbUbNZ4xXXHEFANdccw2Q2j9K25adQQn/xWannXYC3PH26NGjKGWAMhG3\nRBaK2lOjBunMCknOpZRwUEwyG0aZUDKSWeRSPsiPdA2+oiKfcjc6RunEit9VzLWiulSi6LDDDgP8\nOz0mjqOQElH6nzfqqRDpflEgKRk2SjET8vsrGeauu+4C3MZ43kScUaNGZbV7BMUks2GUCSVjzRaN\nGzdOidtVwXxv5FQURO2j9DufUcaTS/8LmMUTmzVbxzR69GgADj744MT9RLWbIOOI5Boqo8sbiy6U\n7rrDDjs4UW66FoqTUPacdGfZN/I5H2bNNowKo+Qk88EHH0z//v0BOOKIIwBXx1QMcJTkOquXUonY\nTMQhmaVjSvp4KbQlO8w1TJc/sO222wIwePBgAP7+978nfR6mKKMfkvYq6BAma8wks2FUGCVnzX7k\nkUec7BRJPb8Y5WJS6hI5Tvwk8pAhQwo8kvCkWzW88sorSa+97VrDSOSZM2cCbtksbUurzHQSWaWy\ngjSRy0TJPMyqlfTiiy9y+umnA4Vz9IehmMvrYrifwHWhHXDAARm/pxv2tttui31MUbDNNtsAqefz\n8ssvB9ySUOrYmEmoeLehtNYg1yrfh1jYMtswyoSiG8A0c2kps/baaxc0TDFft0a2pIhiE4cBTJ0s\n1YHj7rvvBuDoo4/Od9M5UUopkHFgBjDDqDCKLplFOiNAIdLWwszqW265JW+99ZbfdrSNKIeXN4VM\ngSwWJpnrMclsGGVCyUjmYpHrrP6f//wHcAvXm2QuHiaZ6zHJbBhlQijJbBhG6WKS2TDKBHuYDaNM\nCBXpUO7GBR2fwvZUx6khYwawhk/RW7o2FBrSjZBLXLg9zOEptfRWs2YbRoVRmgHFRSLbjFxVVZXi\nTy7k7B3FvjbeeGMAPv7447y3Va6UikQOi0lmwygTTGduQDpzLsShM6upuorXFZuor6GK9W2yySb5\nbioSTGc2jAqjZCSz8pnnzp3rNNmKgmy6bSlL5iB6+Zw5cwDYYIMN0n5eDGt2TU1NSiF8NVRTyaGX\nX34ZgOuvvx6AJ554Iun7iQ34sjXjK+VrGIaBAwcCcM899yS9H1Qyl4wBTBcq3YOcj7Gp0MYM1U+e\nN29ezttQN4SFCxdm/a7fQxwHQa/D5MmTndpXN9xwA+BWp9SDKUNc9+7dAbfggbpKJE4GpdBjLCz/\n+Mc/ALdwQxC8D3FYbJltGGVCyUjmTBTLVRBmReDtHa3KjqqT/Mknnzjf1Xe821fkmbcfUangPQ86\n5qVLlwJuPe1E1GPJu+xWEYr3338/6XUx+lRF4WZUN4wLLrgAcFcaKiel4hsqIig1I0z97GyYZDaM\nMiE2ybzqqqsCsGTJkkDfV0/is846K64hhSbTTK3ZXB0cJZX69esHwKmnngq4utNFF10E1Bt8FPO9\nzz77APDmm28COJ08Ro4cGd1BxIjKOUm6br311infOfTQQ4H6bofgSiLZFp566ikgmh5cuRJWIjdp\n0sS5hpK43m2oPO+jjz4KuMe5xx57AMH6hIXFJLNhlAmxuaa85XP89jNo0CDA1Snff/993n33XQA2\n2mgjwJV60quitG7m69ZQsfMHH3wQcF0wLVq0AODZZ58FYPjw4UC9NJMU0jlS94MXXngBcPsda1WT\njy4Xh2tKur10ZQVZdOnSxfnOddddB7jWbOnCKqMs3fHVV18FYNq0aYC7ouvYsaPGn3U8hXJNaQXV\ns2fPFMm6YsUKAGbNmgXA5ptvDrj3g87Va6+9Brj9rYJgQSOGUWFErjNL2sivuOaaa6b93p133gm4\nOlWrVq2Aet+q9BBJYElozXrFRJJYkkarhYsvvhhwZ2/5S++77z4guVyw15rdtWvXpNdjx44FYPfd\nd0/aV7HR+NRzWHqhV0pNmzaNM844I+O2JKHUe1v+8nXXXTdpX3F4MoJuWz5w6cedOnUC6o936tSp\nAKy33nqA67XQd7WaVAdT7TPOgo8mmQ2jTIhNZ27WrBngzkxCM9aGG24IwIwZMwA36qldu3aOziyp\np9fqnyv9KgrS6VvemTvdTK7jaNu2LeBKlIkTJwLwwAMPAHDaaacByVZ9bU8+SEk4+abPO+88AK68\n8srQx+Mda5Q6s7Yti/Rnn30GQOfOnQHX7qGVRqZt6Fi1gtGq6+233wagffv2QDDdMm6dOZ39RzYR\nXVetto499ljAbZ6n49PzkAumMxtGhVEyiRaa/dK1otlpp50At49uKVmzt9pqKwCGDRsGuFZYvb7j\njjtSfiMLp3Th+fPnA64+Lmu2JGA+7XmilMyyZXijlvr06QPUx2RHhe7L1q1b8+OPP2b7bskkWnjt\nIYoM++6773Lepklmw6gwSiY2+6abbgLqrd+axTS7yUIsvUMZOaWALJ7S7RTpJWt+OhQ1JquwXkvy\nHXXUUYAbPRQkeypOdB3kSxWSQlOmTIlsXzpvWrX88MMPkVqA33rrLbbccsu8t+NNy/Rb4eYjkUOP\nqWB7MgwjVkpGZxYtWrRwLIDKLFG0kHSzCRMmRLa/XPUtr9VY+ct77bUX4Fp6f/rpp6Tvt2/f3omC\nOumkkwC49tprAde6LR25ZcuWgBs9lAtR6Mx+urLiq6XzR4H3fqyurs7qDy6UzqxYgkmTJnHggQcC\nrrfCi1YxsoPkQ4MrTiAWL17M4YcfDkDv3r0B10XVvHnzoo3Li24whR/qtZIkrrrqKsCtHnHIIYcA\n9ceiHs9yX3iDZBR4cPzxxwMwYsSI+A4kA7vtthuQmjS/aNEiIJqHWEUKFBIqdA5atWrluO6KhdyQ\nl19+OVBvwJQL0g9NzIWs4mrLbMMoE0pumZ2Id2wKRkhM9M/E7NmznRC8DPvIa4mmmVeqgCSzkg4U\nVJAYRKIQVyUj7LfffoDrslKoq4JkipVo4bffxYsXA64akA9eV45QZcwg9b3jWmZnkqrZrklQo11i\nLXY/zDVlGBVGyenMkNqwTcaEoBJZZJPKQZEbYt68eU5Ah/ezN954A3ATKxSeKuPV008/DUCbNm0c\n94sqa2pmljtmyJAhSe8XGr/CcjKARSGRhVeCSVIr2KKYnTfCnH+Fp4Y1VkZ5jU0yG0aZkJfO7E1E\niILGjRunuEA0W8dRaiWTvqXCAn379g29XW8hN60uampqnPBUpdG99NJLgLuSkIVcLrp8yEVn1mpD\nLjKtGHbZZZek8eaDzofsBF68BRIzkekaavuJ95QCfT788MNQY07YX8p7caY2ms5sGBVGXjpzHLPR\n7NmzU95TUbxCIz9rLkiapSssoDQ/faYE93HjxgGuVC8GNTU1TmKDt8iiyuaGkczeQn06Zr97R6uB\nqJJp0pWyzVUiP/bYYynv5fsMzJkzJ7JGBiaZDaNMKDlrdufOnZ1+ROK5554ryliisDRKykoi1dbW\nOiGerVu3BlxppGgoRRwpoSRMEf580iX1e/nB999/f8BNyVQhCenOui5KFFFkWOJ4vMfiJ8l0jMVc\nlfihyMN9993XeU+hxvkSZXshk8yGUSaUXARYYilajS3XAumNGjXKWgyvmIntKj3z3nvvAW7xQ5We\nGTNmDOBf0O+oo45ySip5Y5tFPhFgKmovH7kksPBeFxVeHD16tBPBle3aqezSggULgg4rhbiuocaW\nrglgnNZrL2bNNowKo2Qks1+a3Z/7jWu3RZXMKoQn67aKy6vscKIOmitxpkAK+cNVbCET3uZyUTRO\ni/oaeo9XlnW14enQoYMToVYITDIbRoVRMqbD+++/H6jXk72S2GsRbugoKumAAw4A3JXHI488AqRa\ndmWh9kZmFQrlk/tdhyASWUn8UbYwjQqNSQUj1Vrmyy+/BFzJrOKN+Zx/b7mhKDHJbBhlQslI5sSK\nHN4sIll501kVGyKa2aU/SjJfccUVQGrWmD6PYzYPg8atooXnn38+4OZsy9pdU1PjRM8pvj0flImm\nQof5cMnrl701AAALzklEQVQll3DJJZckvaeVhf7q/Cs77MknnwSiWRHFeQ2LbgDTjSrjz08//VQ0\ns3+cBjAFUSSeb/VbkjFFvaV69eoFwEMPPQSUTt3sUiXINTz44IOBerfZjTfeCMDJJ58MuGqP0i1V\n1imx1BOkGu8KhRnADKPCKPoyW5JKpWgKKZULiaRrs2bNnKXW9ttvD8DVV18NuKF948ePT/qNX/ma\npk2bRpImGTW77rprpN0tomD06NHO/xWeqvP6xRdfAG61UV0Pfa57s9QxyWwYZULRdeaA+wXiKaNT\njKAR6WjrrLMO4Lp8vv76ayC1c2Y+mM4cHHWfUBKFEl8ydbUsBKYzG0aF0SAkc5zEJZkzBQfIBeLV\nd+MIKDDJ3PAxyWwYFUYoyWwYRuliktkwygR7mA2jTAgVNJKLcSGfjCfVmnrhhReA3MIa/YxNotKM\nJ+V+jOV+fNm+GPgfUAfUdevWra5bt251el1dXV1XXV1dN3z4cOe9Qv6rqqqq+/MipvzT2Px+m+74\nyumf3zUsp3+VdHyZ/tky2zDKhEj8zFrK/vrrrymJ9FH4TDt06ADAV199Bbipad9//z3glnkJcyxa\n/v/2228VtUQr92Ms9+PLhElmwygTGmQEWLaC78o7XbFiRcoKwfvbSpvVy/0Yy/34MmGS2TDKhFCu\nKZWAVWMxL1VVVSl6a1jdObFoepMmTYDULKJsLiq1CwXYYostAJg7dy4ACxcuDDSOhkIcbXWjQIX9\nVaR/8ODBgL9dwzv+Tz75BHAL65czsvmookmuFH2Z7V321tTUOJUc1a0vbB2pm2++GYATTzwx63ej\nXqKpTpXqVsXBbbfdBsBxxx2X9bvFWmZPmjQJcHtbB53M1ZtavamCYMvsemyZbRhlQk6SuUuXLgDM\nnDkzyG8A/+WVlu4q6LfVVlsxceJEAKdbotCsrWguVYB8/vnnk95PJFsEWlSz+oABAwAYNWpUrptw\nUL9mlbPJh0JK5nySdqQa3XXXXQCccMIJYfZrkhmTzIZRNuQkmf2kbaIRI+h21aN41qxZQL3BSlL0\nhx9+AHA6CqrXz+effw64XRRVrzmIXtasWTPANarFPavrnNx0000ADB061KnLrBWOgmE6duwIuB0d\noyiXVAjJvP766wMwZ86c0L/Vsan2tq5pyG0URDKvssoqQL0+P2LECACOPvpowF1hxoFJZsOoMIpu\nzR46dCiAM9P9/vvvjqRVSVQVJ9fMKN1Ykks9gF599dXQ+49qVveeR1np11hjDQC+/fbbrNuQ3v34\n448DcP311wNwzjnnAK7kU4ePgOOKXTLrWDNlxnl7bSsE2K94oVZZL774In/7298y7j9uyazCi1pB\nJaLx6xwIuVVFPtmDJpkNo8KIvAi+ZiQ5wP0CPI4//ngALrzwQgCGDRsGwPLlyx0/8Ztvvgm4+rRm\na81uKlnrtXoXgmz6rAJrtttuOyCYZD7ssMMA+N///pf0vlYiYSRyITjppJN8P1PrHR2/9zzpmPx6\nO0uCf/bZZ9EMNgd0n3mlbiIad2KwU6ZtxYlJZsMoE0LpzAMGDKiD5FYfXjSLSYr6bT/TfhXxpUZq\nkoKS9notqS99JNHaGJRc9S35Rc844wwApxmZ0Ewd5vwqeuzee+8FUlciuTQui0NnvuqqqwA488wz\ngfRSye/4ZQ9Ry5ds90lVVZXzm0WLFqX9TtQ6s7cftcYm//9mm23GueeeC8C2224LuMera6R7MJNU\nD4rpzIZRYRTMmq2ZSxJNs146xowZA7g9m8XSpUuTXi9fvhxwJXJifHfi60zkO6sHTRwIgl8fZrVH\nUfJBGOKQzH7HLMvu2LFj8+6lnNijW4kIGb4biWTWfSOf99ixYwE48sgjk743c+ZMx54zcuRIwLUR\nqPezXk+YMCHX4TiYZDaMCqNgLV0lbc4//3zA1bu89OjRw8mW0uzsl7YoSeWVwFF0uM8VWaRzwS+C\nLZeoqDjwk8gad/PmzSPfR6YVXNRo9Sg7iDduoU+fPkB9Jpji5iW1VUF2p512AtzIxkJiktkwyoRI\ndeZ0xQlEQgG9tJ9rpuvevbujs8hn7Vfz+thjjwXg9ttvzzJyf8LqW/vttx8Ajz76aNrPZ8+eDcCG\nG24YeAx+urLo1KkTkHPsc2Q6s/faer0JUeDdx5w5c5zjz/CbSHRmXVutGjt37pz0ueL6vbabdEjP\nj8K/HFRnju1h1g2qHrcffPABkGruf/rppwHo37+/sx054pVo4Q0oEPvssw/gBmjIpXPBBRcA8PDD\nD2c9plxvBL9wRL3OtOTUsetcyBXnF7aYTxWRfB5mpZwqMcSLjjGfftLZ7r/dd989qxEpqodZx6Fg\npHXXXRdw3U+PPfYYUF+F1o958+YB0L59+1yHkYIZwAyjwojcNaWlsWo//eUvfwHcWdwrZQYNGgTA\n3XffDcCee+7pSFgFCwSlX79+AEyePBmoX+Jkk2r5zupaPXhT4LRk9gaytGvXjgULFgDBXWiFlsyq\nS+4XpBHFuES2+y/IPqKSzLrfVI9dy+5x48YByfXs/MatxBptIxsrr7xyUs26dJhkNowKIxLJfMwx\nxwBw55138tFHHwFw0EEHATBjxoyM29SsNH78eKBeD/abjb36uPe1pOFLL70EwM477+xIfunPMl4k\n/CbwrF5XV5d1bF6kzydKbhn4pJP6EZHkCy2Zo5CWQSklyRwG77hl2JW+HfG+TDIbRiWRk2SW1U8W\n3cTZU21YVZQvW6C5TPf6603qTkRO+1deeQWATz/9FHD18ixjB1Jn1Eyzepia1Er109iEUh819qlT\npzqfSQdT6OM999yTdsz5kItkVjqqCkcIFXCMopZ1lNI/qmsYlJVWWilFz23Tpg3g2lCixCSzYVQY\neenM6aSd3pPT/LvvvgPckETNaPqrmUz67gYbbJCyX0kCSeJswSTy8TVt2tQJ4vCzHMelbykJJNNK\nQ/qVd5b3ltjJh1wks66FV5pJ11dZ5CB4ywQFTU+NSjLHweTJk50VqMileH9QTDIbRoWRVxxeOqmu\n9xRoLt/dM888A7jRNCpRqiJpmtFUZhbgsssuA9wwRm3bTyKLb775BoCLLrrI2Uahky8ySWThF74p\nqRRFqd1c0LXwWtv9rO+SuonXxdunOyil1jMrHW3btk15Lw6JHBaTzIZRJhS81K4klor09erVC4D5\n8+cD9VJI5YJU9F56dz6oC6E3KaOYrU169uwJwDvvvJP282JZsxN+m/Fz6fze8kZhUDz6lClTQv9W\nFPoaJp6XfP3LNTU1WVeNpjMbRoVRuMzvP5HeJYuo9GHNTuuss44TE5xvv9pE8kmTjBpJXL+Ws2pT\nUyydWWWQZd9Qe1alAIpM2UN+KFOsmAUkcqVHjx4p7+Wb/hnleTDJbBhlQsEls/QrzfKydsov26tX\nL6dcy7Rp0wDYdNNNgezRNdLHta1SRZLWW7BQec1z584F3LY0KgSfqcRxlLz++uuAG1evuPLNNtsM\ncJsThEHN/xqiRBbKBExETfNKAZPMhlEmRB4Blg0VEpelWrqzoou6du3qZDZJd/ZWJ8ln/ypSrqir\nYlqzM7XEBVhrrbWAYK1tMuwj8lK7Oney4MrHqtztL7/80qnSUQgKdQ11X7Zp08bJTyiEXzyoNTuS\noJFMy1uFUZ566qkA9O7dG4Dtt98ecCsgqrDAwoULnROULUnDW34nk2tE28qWCF4I5CYTmrT0cMjw\n51eVtNjk0lmjIaNCA7ovly1bVpLBLbbMNowyoWBBI5rJZAhR2GYubhe5t7Q099K3b1/ANShlopjL\nbD/y6eXrpRD9mYtNXNdQaau6j5Q89McffxTUXWhBI4ZRYRRMMg8ZMgSAW2+9Nds+As96YXpK+VGK\nkjlKTDLnjtdY2qFDB8BNDioUJpkNo8KITTIHdRu1a9cOcIuHd+rUySkoEBaV8w3ScUCYZG74VNo1\n9MMks2GUCaEks2EYpYtJZsMoE+xhNowywR5mwygT7GE2jDLBHmbDKBPsYTaMMsEeZsMoE+xhNowy\nwR5mwygT7GE2jDLh/wEPx/uC4lrkrAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19746d350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 3250, D: 1.366, G:0.775\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n5IPjCkiScQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1968da1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 3500, D: 1.354, G:0.7631\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff196a63710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 3750, D: 1.369, G:0.7178\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff196a73650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n"
     ]
    }
   ],
   "source": [
    "# Make the discriminator\n",
    "D = discriminator().type(dtype)\n",
    "\n",
    "# Make the generator\n",
    "G = generator().type(dtype)\n",
    "\n",
    "# Use the function you wrote earlier to get optimizers for the Discriminator and the Generator\n",
    "D_solver = get_optimizer(D)\n",
    "G_solver = get_optimizer(G)\n",
    "# Run it!\n",
    "run_a_gan(D, G, D_solver, G_solver, discriminator_loss, generator_loss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Least Squares GAN\n",
    "We'll now look at [Least Squares GAN](https://arxiv.org/abs/1611.04076), a newer, more stable alernative to the original GAN loss function. For this part, all we have to do is change the loss function and retrain the model. We'll implement equation (9) in the paper, with the generator loss:\n",
    "$$\\ell_G  =  \\frac{1}{2}\\mathbb{E}_{z \\sim p(z)}\\left[\\left(D(G(z))-1\\right)^2\\right]$$\n",
    "and the discriminator loss:\n",
    "$$ \\ell_D = \\frac{1}{2}\\mathbb{E}_{x \\sim p_\\text{data}}\\left[\\left(D(x)-1\\right)^2\\right] + \\frac{1}{2}\\mathbb{E}_{z \\sim p(z)}\\left[ \\left(D(G(z))\\right)^2\\right]$$\n",
    "\n",
    "\n",
    "**HINTS**: Instead of computing the expectation, we will be averaging over elements of the minibatch, so make sure to combine the loss by averaging instead of summing. When plugging in for $D(x)$ and $D(G(z))$ use the direct output from the discriminator (`scores_real` and `scores_fake`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def ls_discriminator_loss(scores_real, scores_fake):\n",
    "    \"\"\"\n",
    "    Compute the Least-Squares GAN loss for the discriminator.\n",
    "    \n",
    "    Inputs:\n",
    "    - scores_real: PyTorch Variable of shape (N,) giving scores for the real data.\n",
    "    - scores_fake: PyTorch Variable of shape (N,) giving scores for the fake data.\n",
    "    \n",
    "    Outputs:\n",
    "    - loss: A PyTorch Variable containing the loss.\n",
    "    \"\"\"\n",
    "    N, _ = scores_real.size()\n",
    "    loss_real = 0.5*torch.mean(torch.pow(scores_real-Variable(torch.ones(N)).type(dtype), 2))\n",
    "    loss_fake = 0.5*torch.mean(torch.pow(scores_fake, 2))\n",
    "    loss = loss_real + loss_fake\n",
    "    return loss\n",
    "\n",
    "def ls_generator_loss(scores_fake):\n",
    "    \"\"\"\n",
    "    Computes the Least-Squares GAN loss for the generator.\n",
    "    \n",
    "    Inputs:\n",
    "    - scores_fake: PyTorch Variable of shape (N,) giving scores for the fake data.\n",
    "    \n",
    "    Outputs:\n",
    "    - loss: A PyTorch Variable containing the loss.\n",
    "    \"\"\"\n",
    "    N, _ = scores_fake.size()\n",
    "    loss = 0.5*torch.mean(torch.pow(scores_fake-Variable(torch.ones(N)).type(dtype), 2))\n",
    "    return loss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before running a GAN with our new loss function, let's check it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum error in d_loss: 0\n",
      "Maximum error in g_loss: 1.45919e-07\n"
     ]
    }
   ],
   "source": [
    "def test_lsgan_loss(score_real, score_fake, d_loss_true, g_loss_true):\n",
    "    d_loss = ls_discriminator_loss(Variable(torch.Tensor(score_real)).type(dtype),\n",
    "                                   Variable(torch.Tensor(score_fake)).type(dtype)).data.cpu().numpy()\n",
    "    g_loss = ls_generator_loss(Variable(torch.Tensor(score_fake)).type(dtype)).data.cpu().numpy()\n",
    "    print(\"Maximum error in d_loss: %g\"%rel_error(d_loss_true, d_loss))\n",
    "    print(\"Maximum error in g_loss: %g\"%rel_error(g_loss_true, g_loss))\n",
    "\n",
    "test_lsgan_loss(answers['logits_real'], answers['logits_fake'],\n",
    "                answers['d_loss_lsgan_true'], answers['g_loss_lsgan_true'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter: 0, D: 0.3726, G:0.4073\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197824910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 250, D: 0.7319, G:0.3646\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nS5YWkfwwZ8nSIvIPYdjdE1LIvWUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197258e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 500, D: 0.2219, G:0.2428\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1969cde50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 750, D: 0.2219, G:0.1592\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztnXm8ldP+x98nXZXTJCIJmWeSkH5IhggZE26GSKYykynX\nGBHRNZTxurlR4UZlOJJLMiRj5CYRCkkqDaLB+f1x7udZez9nT8/ezx48+/t+vbyO9tlnP2vt9Tzr\ns77f9V3fb0V1dTWGYfz5qVPsBhiGEQ72MBtGRLCH2TAigj3MhhER7GE2jIhgD7NhRAR7mA0jItjD\nbBgRwR5mw4gIdYO8uaKiInLhYtXV1RX6/6j3D6Lfx6j3LxWmzIYREexhNoyIYA+zYUQEe5gNIyLY\nw2wYSWjTpg1t2rSp9XqdOpk/NvXr16d+/fphNisp9jAbRkSoCJKcIJ9u/7XXXhuAlStXeq/99ttv\nALVmNs2Mf/zxR87XLbdtjUL3cc2aNYAbw1WrVoV+jXyPYUVFRdzP2PtOz8+UKVMAaN++PQBXXXUV\nAAMHDox7XzZkujUVaJ85n6xevRqAtdZaizvuuAOAjTfeGIC6dWuaOWTIEAD69OlThBYayVhrrbUA\nqFevHgArVqzwbviRI0d6rwEsXLgQgA022KDQzcwYPbQNGjQA4D//+Q8ACxYsAOD999/n2muvjfub\nvfbaC3AP7V/+8hcA3nzzTQA6dOiQ51bbMtswIkPJLLNFr169ePjhh3W9fF8ub0s0rSa04pAZ0aNH\nD1544QUAfvzxx7Aul5R8LLNnzZoFQGVlJQCbb745AL/++quuEXv9uNdmz54NuNXViy++GPdZy5cv\nD9yebMdQS3+Zc0KmwVtvvQXA888/D8BNN90EuLFNhFYk/pVJly5dANhuu+0At0LJxFS0CDDDKDOK\nrsyyLc4880wAhg4dGvYlUpKrMvtndynQIYccAjjlET///LOnbHKWJHL+hUU+lFn24UsvvQRA06ZN\nE10XgMMOOwxw38O0adMAePfddwGn0Ln0PdsxlK0vJRY77LADAGPGjAHcykP36qpVqzwn7KeffgrA\nrrvuCsCiRYsAaNSoEeCU+bTTTlP7El4zFabMhlFmFE2ZY2e5ZGi21ns1G4aZ6ztXZVYbpa7J2jZz\n5kwAdt55Z6/Psqfvv/9+APr27Zvwb3PxHYShzNpmufXWWwGnxFKhX375BYAmTZroGt7fXnTRRYCz\nN7fYYgsApk6dCjiP8YYbbhi0WR65juHxxx8PwFNPPQW4+0zj1KlTJ8B5tXU/gvtu5N3eaKONANh2\n220BGDRoEAD7778/4BRZ31Em97Ips2GUGUW3mROx3377ATBp0iQAli5dCrhZLZGNli3ZzupSo8sv\nvxxwtr5mdb9ijx8/HqhRr3333ReA9ddfH6ixo8Htq3/33XcAvPfeewC0a9cuYK8cuSiz36aUmqi9\n8vKefPLJANx8880ADB48mM6dOwMwatSorNueKUHGsKKiIq0arrfeeoDbG37uuecAqKqqAmrGWiuK\n0aNHqw1xnyGPt747fZdajQXBlNkwyoySVGahth155JEAjBs3Lh/XyEqZZRt9//33yT4XcDNyqu9Z\niicbTX/TrFkzwNll/fr1y7R5se0IzZut9vz000+Ai+I66KCDgGAqPGLECKBm3z1Xwo4V6Nq1KwCv\nvPIKAC+//DLgxmHy5Mm1xtW/Xyzl/v333xP+PgimzIZRZpSkMsur+9prrwHO0zlx4sTQr5XtrC77\nVrN4sv3xTDzR/iipefPmAc7jq2tkQ5jKLHtP7ZR/4OyzzwbwIvdGjRrleYiFVh2xnuCwCEuZTz/9\ndAAvQu+HH34AnA9D0Wvt27dnm222AeDrr78G3EEL7cEL/6Egf2RgJpgyG0aZUZLK7N9f1gzZsmXL\n0K+V66wuT3vDhg3jXtcpoXXWWSdIW+L+HUZsepjK3LZtW6Dm1FAsixcvBlzkVL9+/bj44osTfoa+\nL3nyZVPmQljKLBX95JNPANcfjYviqZs1a8Yuu+wCwGeffea9Bi5moHv37tk2oxamzIZRZpTMeeZY\ndPrmlFNOAfLjxc6V1q1bA9C4cWOgtrdSNlUuZBIlV0g+/vhjAC677DIADjzwQAAOPfRQALbcckvA\nraQSIQ+4P5a9FNAY7rHHHgC8+uqrAOy5555A/Hho9SjV1lnnE088EYDHHnsMgJ49e+a/4f+jJJfZ\n+lKD5FrKllyXaFpGa1kd5PvM9L3FDudMRiaTzW233Qa4Qwtvv/024BIZaJkdVh/D6J/uOx2wUOCH\nDsaMHDnSa78CTHR0U4k15BSUMOWSB8yW2YZRZhR9mZ0o4DzV4e9SQzOv0PbMQw89BLiAAy3HIXMV\nKqUlaCIUOKElZ/PmzYEaR5FWVzrgf9999wFunMNQ5HyhtitsVT+lxvXq1fPaL4ee+nXXXXcB7lCK\n3zEqkh2/zAVTZsOICCVjMwc5EhYm+c7sqG2bRMcDdVgjVrUBb1vn7rvvzvn6hczOqaAK2Zqx6Ajo\n1ltvDcDRRx8NOOdmsmQOmVCoDKv+o5CxyH8gFddBk48++giA+fPnA7XHOhPMZjaMMqNklFnMnz+/\noGlY8z2r+0M1ly5d6h0cOeCAAwDo379/3N/o0L8CEXK8fkmUdL3lllsAp8g6vK/Xr7vuOiC7AwmZ\njGE2udalokuWLIl7PdZmFlJmhR7ruORXX30FwLJlywA46aSTAJfYb8aMGWnbYcpsGGVGybmNg6jy\nZpttBsA333yTr+bkjN9b26hRI292vvLKK+N+p35ozzpK6PDIJptsAjil7NixIxBOdZJUZPP5fkUW\nq1atquXjUQK/119/HXD35lZbbRX3e3m3pch169bNKmFBIkyZDSMiFN1mPvfccwHnxdSRskQMHjwY\ngEsuuSS06xej1lSyAxV++zqkaxXVZpa6KdWT9lVlY0qVdtxxRwCmT58e+Br5igBLpuYVFRXeGMnf\noQMWStygpPdakSi9kMJ8gxyFNJvZMMqMgimzIqN69+4NZLafrL1Z7ccqakazYhi2RjGrQGq2Vnyv\nDi6EqdBhKrNSJaU6SBFzHaC2ukm5FC0Wdh8z6V+ymAZFsimBnw5NyM6XT6Nhw4ZeRJsOA4kvvvgC\ncPvp/uSTupeDYMpsGGVGwbzZKj/jt5U0O8baKf49OO1Jfv7554Vqbl5RJJFO4WjmP/zww4HSjFcG\np8haSSjaSSjl7jXXXOONoR8p8ty5c/PVzMDo+1a/FLU3efJkwEVxnXPOObX+1p8OyZ/kX+V5VKYm\nn5gyG0ZEyLvNHCTSxU+LFi0A5xHMB8WwmWVHyrPrL9CtVUsYye/CsJnVDqWPVSzAt99+C7j+aA91\n1KhRXmxygvYArnjAnXfeGbQ5iT4zpzFU3LT6p8IF6pdOxsmHs3jxYs8Wlqor0uvRRx8F3CkxRX5Z\nql3DMDKm6PvMYZJNmp1S2Gf2I7tSqWhErv2DcL3Z2jOVB1f92n333b3SOkL7zddffz3gzv36UYI8\nJdPLhLDGUJF3RxxxBOBS7ipSTz6Cvfbay/MPaHVy9dVXAzBhwgTAndf2j7U+Q/Z5JmSqzCUXzpkL\npZIrKxXV1dVeAL8OHQwfPhxwW2/JlmTF7p9/S0rHGv28/fbb3vJT1S50bDDdYfwgD3HYaJmttsts\n0Peu11u0aOEtuXfaaSfA1WlOR5CHOCi2zDaMiBCpZXY2FGqZHRvoIgWWY0XLuW7duoV+3WKEc2ZS\naTFMihn4UwjMAWYYZYYpc5nN6lHvY9T7lwpTZsOICPYwG0ZEsIfZMCJCIJvZMIzSxZTZMCKCPcyG\nEREChXNG3e0f9f5B9PsY9f6lwpTZMCKCPcyGERHsYTaMiGAPs2FEBHuYjaypU6eOl4ixmJ+RL2KT\n3ftfL0VK81s0DCMwJZ1p5JFHHgGgV69eca+rGNesWbMK3qYwUfTd9ttvD7ikhz/++CPgyoOWKv6M\nKLEJCdU3JY7fZ599AJgzZw4AEydOBFwqWn+J1FLAHx2pLChKbQQucb4Kw/nTBSlbyfLly/PbWEr0\nCKS/4sDSpUsB2GOPPQB303ft2hWAcePGZX2tfO9RKie2buL/XTPl34RZeyqf+8xq1zrrrAO43Ocr\nV65kzJgxADz77LOAy8apm16ZVzt06ADAW2+9lXU7CrXPrH7++uuvXgbPfffdF4BXX30VgGnTpgGw\n88471/qbbLF9ZsMoM0pOmWPbo1q3Wob26dMHgKeeekrtAVwivIULFwIuv3GG1wt1VvdX6NC/tRwL\nkgtbfyMVuPfeewE4//zzg7QndGX2J7HT919ZWQnA7NmzvbzSffv2BdzYvP3224Crq/X0008DLpme\najRJ4bQqS0XYY1ivXj3ALZn9VSHr1KnDCSecAMCTTz4Z6LP1Wbp30yU4BFNmwyg7iq7M6667LuBm\n7iDIAaZaVNlUDciXvaUqHGE4sfJpMyeriJiqHX5bXulje/bsCdTU2lZObdGvXz8AjjrqKMCtLv72\nt7/525u2HX7CGkOtMJKpZZDvKkxMmQ2jzMi7MsuLJ6+ekF2imjzafurUqRNvvvkm4GxGP6rOp+0O\nzagiiELnOqsn8zjr9TPOOANwNYhi3+f/7hctWhT3UxUF0yXHT9O+nG3mZIq18cYbA24V0rp1awC+\n/PJL7z2qm6XPePDBBwE477zzAGdD+quCBlHBYp6a+u233wB3P+cjoMSU2TDKjKLZzJqRM/HmydOp\nWTCZxzgb8jWry+P7ySefJH2PvL/+PciqqioADjnkkJzbUYjzzKr0KXWdO3eu1+/ddtsNgI4dOwLO\nm60gCnmMc7FHi6HMqqXVrl27vF/LlNkwyoyCh3OOHTsWgCOPPBJwoZmxdpaQEqs636RJk+J+X4rJ\nCDt16gTULpQm+1dVA4GkBwxUBbJU8e+7zp49G4gPyVTo49///ncA+vfvD7hdi/r168d9Zqqx9F+v\nFJAiqx+6V7MhLC+5KbNhRISi2cy6rrzcUt8FCxaw/vrrA3DiiScCLsrmiSeeAKBHjx4AHHfccQA8\n88wzubQjL/aW/3uNjR5K5vkuhCc0jD5KKRWZ9/nnn+taQE0NZtWWlv0v23n06NFAcl9Jur3eRBTD\nZvavFvK5B202s2GUGUVXZp2Ekndw9erVDB06FHDKrBhtKXGYChb2rC5lkWc3EePHjwdcNJROf+mE\nUb7697/PDm0MDz30UMDZzDrueM8993geetnR06dPB9wKTAodBsXcZ1bcvFaTm266KQDvvPNOaNcw\nZTaMMqPosdlSoS233BKosbE233xzAJ5//nkAjjjiCMDtUcpjHMaB9nzN6jpVM3LkyETXBJJ7s5s1\nawZkF6+e4FqhK7P/tJo8ulKpTTfdlN69ewMwaNAgAL777jsg3ncAsGrVqlybE/oYlpr3PFNlLvrD\nnIhkbdLyVMvSkK6V1yWaboyWLVsCNQEVcu74g140Wf3f//0f4B5mPdzZUIwk+A0aNGDmzJkAnHvu\nuUC8GQV4DjIdlVy8eHHW1yvGMjvZ2Bx00EEAfPTRRwD88ssvQG6Tli2zDaPMKLoyv/HGGwC0b98e\ngLp1a8exKAXLsmXLAPj6669Du36+Z3V9v0qXs2jRIi9BQbLldpjbG4VQZo3d+++/D9QcgNHSW8Ey\ncmr6t+HCWMqGPYYaH7VRfVC6KqidoMGPTA4dFgorXDUVpsyGERGKrswiUeCEXlMgv+ywfClXPvsn\nmylV2iBt2+hgicglZLCQNvP+++8P1GwlyjkmX4HCWJPZyKV00EKqqvRTOhQybNgwAE499dRaqYWE\ntqjkEwgDU2bDKDNKRplFbHvCTDmb4noF9YS2adPGy7sseypROt6wyKcy+0MvNT7vvfceF1xwAYCX\naCLdWGYSbJOMTMYwm/RI/u1FqfFvv/2W8b3oT0ecTf5sU2bDKDNKTplXrFjh2Yj+2e+6664D4IYb\nbgjteoVW5oqKCtq2bQs4729MWwAXxqq0szfffHPW1ytEEny/Z/qCCy7wVh2yM/1/IyU++OCDgZok\ngNmSr6ARpXSWn0PHdidNmsR+++2X0WcpVXDjxo3V1sDtMWU2jDKj5JS5urraS6cjG1KpXPN0vYIq\n8zrrrOMdQvjwww8BdzwwmT0Z5h5lGKlopVTyriuxn15fe+21PWVW3IDSIh9//PGAS34f0y6guOmS\nJ0yYALjdEyVYWLJkSdz7KioqvGOf55xzDuCSUcgDrsivMDBlNowyo2DK3K1bN6D2jOxnxowZXlL7\nBNcHwknVIsKa1fU9pkuL265dO6ZOnZrwd/nw3ueizP72KAXw7bffDrhiafq9kvhVVlZy5ZVXAi6F\nsuxPxWqfddZZgIsMS3ftVIQ9hkKedUUexsZh6/jnc889B7i9adnbV111FQADBgzItjmx7TJlNoxy\nomAJ/aTIKteiGsRCs2Ls6RLNzqeffnrce8NQ5LDxK4nK7nTp0gVwKY9SoT3IfOynByHZ0UyVYX33\n3XcBZ2Oqz99//z1Q48G+8MILAVef+K9//SvgVi5+L7efQiRr9I+Zjm2qQN+QIUMAuOaaa4CaE28A\nrVq18hL+S5GFVmTJFFk+hGz209NhymwYESHvNrP/7K5mQ8XqtmrVKu71WPSezTbbLOhlMyas8jS5\noP1keXzDJAxvttICDRw4EHDpjbTfL0+uzvI+9NBDHH744YBTb53VDpKoL1NyHUN/wgQh73wYCRRy\nwWxmwygzCubN1nV0ikb2VSpU9lM2TD4I2xMq5fEXs0tFpjZyNiVRwtxnVoE4Ja2TjTlmzBjAxR/P\nmzfPO/klD3imNqL6pr5mQlhjqHJASg+cD3TKSnHemVCyaYOmTZsGwC677JLw99XV1QV1AIUdNKKb\nWMcZE1zP61+bNm0Al2ImH+Qzb3ay7bdWrVp5zqJCUMzsnIXAltmGUWaUXDhnoSm3WT3qfYx6/1Jh\nymwYEcEeZsOICPYwG0ZEsIfZMCKCPcyGERECebMNwyhdTJkNIyLYw2wYESHQeeaob8hHvX8Q/T5G\nvX+pMGU2jIhgD7NhRAR7mA0jItjDbBgRwR5mI2vGjh3L2LFja72uBBR/dioqKoqeXDEI9jAbRkQo\n6fPMJ598MgD/+te/4l5XChqlLc2FYm5r6Lv/+eefAVeou1GjRoArOpbjNYq6NaVsJCNGjADglFNO\nAaBTp06ASwaYC8UcQyXGX7hwoa4PuHTQQdIDJaNk0wblgj9bYi41mES+bwTVXFIGzm+++SZte8Os\nbFGIh1k5wgcPHgzApZde6uV4U80lfQ+qG6Z8YWHkkS7lfWb1T7nhrAqkYRhpKVhFiyCoSoBmc5FO\nkVWBT1UWi5HvWG3ST//MnM1nhFl7KgjJkhNqCdm1a1cAOnToALgldM+ePb33agw1pn369AGcKaGx\nUgUIVY8oddKtKFSD+4MPPgBc/6+//noAz3H4zjvvhNYmU2bDiAglYzPH2sPpUrmGYSuLfNlbYR4t\nLbbN7B8P5QTv378/ANddd13c73fccUevtpQUd/To0QCceeaZagcQPK92IvJtM6u/m2++OVDj93jm\nmWcAV29aq0C9d5999gFc/TCtQKZPn642Z3x9s5kNo8woGWVOhL9tO++8MwCffvqp2pPwfQGvEUqt\nKb966nXVWNp7771rvU9VG3bfffe432mrStsexVbmFJ8NONVVbbDLL7/ce8/f/vY3wClV586dAbcS\n86t7lu3IaQyT3Udakdx///2Aqy1dXV1N06ZNAbeyEEr+r6of8i907Ngx7veqhvr++++nbZ8ps2GU\nGUVXZnn5ZG+tXr26oN7bfNlbL730EuDqF4kVK1YwcuRIAM4444ywLpeUoMpcUVGRdKUjpZKK/vvf\n/wZceR3VnOrevTtXX301ADfeeGPK9qXzj2RCvsZQ95/sXbW1qqrK8+TL4++vGS6vfb9+/YAaPwLA\n/PnzAbfPngmmzIZRZhRdmbPhmGOOAZwSyOZMZH+ks6vDntW1b9i+ffu46yabwRMRRlSUCMNm1neo\nVZRs5B49egA13l1w4aiZ3FMKc5Taqc/ZhLCGPYZHHXUUAJMnTwbgscceA9y+eir0Hanao9//IW93\n7HeULK5CmDIbRplRcGWWqiow/fXXX0/7N+mUSsqhWT5gtFUos7rf9kv1vSbzfOfDRxCmN1vfq9qp\nn48//jiAZye3bdu21tHIxo0bA7BkyZKEny110hgHsaHDGkPZsdobFhpbqWqi+7BVq1aA81Y3b94c\ncKpeWVkJOC/3FltskXG7TJkNo8z4U9jMUgDNiP643lwI296SoqRSWbV/2bJl/rak/dughKHMSjbw\n2muvAe4EmJCtJ5u5srKSefPmJfysu+66K+6nvLuZ+BKSEfYYSomHDh0K1JwCg9rjlaQtgPMjtG7d\nGnC7GlVVVYHbY8psGGVGwZVZJ2u01xrkZFOvXr3i/mb48OG5Nidve5RaRcjOiuXss88G4MEHH0z4\nt1OmTAFgr732yrkduSizVEU2pPaTN9poI30W4KKgFNW0Zs2apDavP3JKe+3/+Mc/Mm1WLcIaQ9m5\nimTzrwRTIZt5zpw5ca+feOKJAIwaNSrbZpVOcoJsQi5/+OEHwGWj0M0zceJEAPbdd1/AfVHnn39+\n0GZ5FOpg+5AhQwC48MILvde0xNQWyNFHHw24ZV6pJCdQeOawYcMA9+Ddd999QLBsIeqTHnb1NcjW\nXYLPzGkM99xzT8CF1+pIp0JxEzlUX375ZcDdi5q0Fab68ccfA7DLLrsArp/ZYMtswygzCr7MVrD6\npEmTAJdyRkfDHn74YW9m1DJn2223Bdz2hULktBWSC/lWZr+6xoZLduvWDYCnn34acFtwDRs2BGDx\n4sVhXD9rZe7evTvggkT0/b/44ouAUyWpkX9FEUubNm0AF1SjoBEFV9x9992AS06g1Zi2elKR7Rhq\nya/vWWOkVEezZ88G4LPPPgOgS5cuQM2yW6ae+jFjxgzAOQe18vDnALO0QYZhpKXgyqztC4W3yW6U\nQ6RevXpegMHtt98OOCeJFEwHwks5OYEfzf5SgyRtUTsyej0T8nEE8qCDDgLcyklbVgqQiE0bJKRQ\nfptYCid1z7WPYQT+3HnnnYBbKQ0aNAhw202NGzf27t8vv/wScP4O3aOnnnoq4FY1uWDKbBhlRtGC\nRmQHz5o1C4DDDjsMqEl0piRoOkAR5sEDP6WYpnXgwIGA8wmEdTwQkvdRK6YFCxZk/Nmy+Z999lkg\nPp+5f6wUKikbWL4SofdLofX+TAKDMhnDIPeQVge6/7RFp6OfO+20k/debTnpuwgjl7sfU2bDKDOK\nlmpXRwR32GEHwB1n/P3332t5MJPNpu3atQPc/uCfHf8q6YorrgAKk6QhiCIL2Yd+Eo3XP//5TyD5\nIZjddtst7t9hhOqma1MyNA5SZK0UlbZq9erV3r6yYiKUWveFF14A3ErT7zHPJ6bMhhERCmYzywY6\n4YQTABdF9NNPP+mzgZporieeeMJ/3Wwvm5Zi2sxKu3PssceqLWpH3PukmrJrgxCmN1vtOvzwwwEY\nP3580vd+8skngLMv5QnebLPNAHdoX+r31VdfAbDBBhsEbldYYyi1PfLIIwG3WtTetyLdJk2aVCtM\nd+ONNwbwyvKEidnMhlFmFMxmVrC+bCYdzp42bRrg9i5feOEF7/hcixYtEn6W3vvKK6/kr8EBkaqm\nioIS+g7877355pvj/i0lzEaR84G86mp//fr1AWfbK+F9nTp1+PrrrwGnzFJkfYYKyKn0jQ5pFBPZ\n1WqT/DqKa7j33nuBxIdn/McjFemoY5SFwJTZMCJCwWxm7b/17t0bqD1j/fe//wVg++23Z8KECQAc\nfPDB2V4uY8K2mfV9KopInvYnn3wy48/Q/vKtt96aa3NCtZm1QlCfDjjgAMDZu/LsrlixIq6UCzhl\nlqprvOUFzqXIX9AxlLL6Peva41bbZ86cGfd7xWw3b97cs/kzOR6ZK2YzG0aZkXdlViyu7CsRRvLz\nMAirPE0YqJTLTTfdFNpnhqHMTz31FOBWVffccw/gIqKkyDoB1aRJEx599FHARfopDbLOAY8YMQII\nZ/xzHUPZyIq31r91Sky+C6VHqq6uzmtUoh9TZsMoMwpmM/tT4YRZllVMnToVgD322CPjvwnLZlY/\n0nniE6FItnRFxLI5PRWmzXz66acDLkZAe8TyXMciT7BWYLIxP//883TtVTszbldYY6iVhU54nXba\naYDzd8QmqW/SpAng7OhMeeuttwCXzSQTMlVmqqurM/4PqM73f/Xr18/7NWL/K3T/qmsuVA1UV1VV\nVVdVVRWsf4Xq41lnnRXpMVy4cGHR+pfqP1tmG0ZE+FPkzc4npXgEMkzykZwgHfXq1fOWrPkwp/yU\n2xgmw5TZMCJC0Y5AGtFFqgyZK3IhFDzqmDIbRkQwZTZKAlPk3DFlNoyIEMibbRhG6WLKbBgRwR5m\nw4gIgRxgUd+Qj3r/IPp9VP9SbXX92bbBMg0aMW+2EUlSPahhPsSlcpQXbJltGJHBlNkwssC/VE9W\n7K+QmDIbRkQo2sO87rrr1ioeFiUqKipyTt5fp04dzyYzCs+AAQMYMGBArbHs0qULDRo0oEGDBt7v\n/GNVt27duP9EGPdFMuxOMYyIUNLnmZVYbZ999gFcWh2lb1F6l1zsk3xvTaXydl544YUA3H///YBL\nN9u/f3/AJcXPhWJvTSVLLeRP0ZMLuY6hlNJvB/sLG6h0zvz5873Xpk+fDsBDDz0EuILzd911FwBn\nnXUWUDuVcGwiwHRbZZluTRX9YdYSRDf7H3/8wXfffQe4WkznnXeerg+4L3f48OGAq1KfDfl+mBMN\n1JZbbgnAt99+C8Bll10GuBteOae22247wOXNymbSKvbDLJSdVdlahXJwKw9aNgQdQ//D659o/ctg\n5fxWHvdJkyZ59ackLMoFtvfeewOw//77A65yi+qQ+7N5VlRUpB1XS05gGGVGwZX5jjvuAJwaaRbU\n7Dd79mzvvZrF5s+fD8Brr70GuFpTffv2BVyVvnHjxgEwcuRIwC2BUpGtMidbGin38sKFC+NeV7WE\nKVOmeMo1x3tpAAALn0lEQVSsipjqp/r+4IMPAq7G0TbbbAO46otawi1evDhtsEIxlLmqqoqOHTsC\nrvqnVlOqJiGF1jJb98X5558PuFrIn376adrrBR1DrRJUuVEVOdQ23T9nn3024KpCdu3aFYCtt97a\nq+4xZMgQAH788UfAVb9UPWaNj7LSqpKk+j1nzpxay/pU/UuFKbNhRISi2cxSNuUfViXBJk2a0L17\ndwDeeOMNoGYrAOCcc84B4L777gOcffLZZ5/FfWaQukX5spmlRLvtthsAw4YNA6Bp06belpxyKLdp\n0waARx55BHCKoO9B9taSJUsA5zzy10pKRCGUOZntmQi9x7/lptefeeYZAE466SQgeB/9/UtWVyq2\nDVo16b6RH2errbYC4JJLLgFg0aJFAAwaNIhdd90VcCsHrSS0GtR9rWofv/76a9w1YtpuNrNhGPEU\nTZlVt1dVAgcOHAhAnz59ks70qm2kLRtVVpCdtXTpUsDZRNraSkWuyqxts8mTJ8e9rooOsh01k/fv\n39+zI2VfCc3eRx99NADXX389AKecckrc76XMUopUhKHMuq7a7UfjpHtp+fLlNGjQACAuYCIW/9aU\nf6y1kunTp0/a9qUaw0S+Df9raqO/bvakSZMAVwNszpw5QE11SKm5dlS23357wHmx1T/9W7ayvN+6\nR1euXOld12xmwzCAIiqzKuxpr7Vx48YAPPDAA95srNk9WR1dzeb+/efYmkDpCNtmlo2mGr/aR5XH\neuHChd7e49NPPw3ARRddBDil7devH1DjFQZXy1gVFfWZmZBPm1nqKRs/FX7183twL730UgAGDx6s\ndmbcjiBj2LRpU8/TrPtF19LYqU6Y7Nt7770XgBdffBGoiX9QYI/a7X+O9Nna3Vi2bFnctXQ/rFmz\nJvCORDJMmQ0jIhRcmWUryKbQHp/2UjPxRMvOknLLpguiyCJsZZaqjho1CoBjjz0WgKFDhwI1+6t+\nb2ls9BvA2LFjAbj44osB51eYMWNGreulOxyfD2WWuh522GEAPP/884Ab29goJ/VRVUClVH5UPXOj\njTYK3J4gYxir+FJi/3cof4d2SW699VYALrjgAu/vdM8lQ/2Qn6FVq1aA28HQyhTcfZvs3jdlNowy\no2DJCTQjVlZWAk5NtWesqK7bb7+d3XffHXAz1oYbbgi4KBupemwle8Dbv83Eyxs2mmmlMFKiQw45\nBHAz9BVXXMFtt90GOH+BgvSl6tp3lid85syZgNsBiI2KKka6mgULFgDw0ksvAW6PVUr3wAMP0KtX\nL8DtkUuRFc3Xtm1bAObOnQs4JZOqJ/OC50psLLS+O11T0Vyq760YAcU5yA/SsGFDPvroo7i/Vfu1\nr6x+qh9NmzYF3GGN5cuXAzUx3WEdczVlNoyIUDBl1mzoPzVy5plnAm5PtUWLFrVs359++glw3t9u\n3brFfaYohiILtVm28o033gjApptuCjiP9Lx582jUqBHg1PyWW24BnAJrlp8wYQLgVjWZxCkXAq2U\n9P3L1tOKKdb2087DAQccAMCrr74KuJWZ32udL0VOFAmma/uPae65556A81XoGKNs5tWrV9e6j3WP\nanX18ssvA06ptarUPRq7px3W6sqU2TAiQsG92ZqpdUZX+3T69+rVq/niiy+A2sqrv5W3V7ZMLoTt\nzZZPQJE/77zzDuA88GuttZZnP8pe1Gkc/dQ+qFYtYSVfgHD3mf3Rb7Eqq4goKZP/FJmUKQwlztab\nvckmm8S14dxzzwXguOOOA9z9NmDAAABGjBgB1NyjyaILd9xxRwDefPNNwCWgePbZZ+PeJ5t5zZo1\nocVmF/xhzuRguBxgugHkVLr88ssBuOmmmwB3jC7WzR+UsB9m9Us3gpZjsaGDCgvUclsOJU1ocprp\niOc999yTdXuKlZwg3X2l70lJCYIEwiS4VqAx1JJbP7U0lgmg7USFaspEir1X/YEmmqw1hnqvTKb9\n9tsPgA8//BBwJknDhg29yTuT/qXCltmGERGKHs6pJZoOb6+33nqeImvZqWW1tne0daOlTC7kS5m1\n3dCjRw/ABU/07dvXS7LgP/Su70A5wbS9kQuFUOZjjjkGcGmeEiGTQqGSWrmEQbYHLXRwR1tSWiJf\nffXVgEvv5D/OunLlSm/FpcClrbfeGnDHdE877TQA3n33XcBt0SkARff/rFmz0gY7mTIbRplR9IR+\nQiF0chhB7TC7G264AYC7774bcG7+I444AoDx48cHvm6hCsdNmzYNqAmWUL80a/fs2RNwyqCEfv6D\nJKWe0C9RdQe9JmXWYZF04ZABrxvIAeYP0pBKKo2QUlpJMZWW6tprrwVqbGy/70cKLf+H/Dk65qoV\nie5zje2SJUvsoIVhGPGEoszZVMKT909ePTFu3DgeffRRAMaMGZPw8/W38gY3bNgQqJ2bORPypcz+\nmVvbH3PnzvXaLTta3mp5UcOkkMqcaIdC6ib1y0c1h0zGUHb9mDFjah320f2kNuo4rrZNlUBR21HH\nHnuslx9bATJKEySbuXfv3oDz8ygVr1Zfen3p0qWWNsgwjHhKxmYWp556quflVdim0Ka+KlvocLyC\n9v0ETTBeiP49+eSTXr8UPCL7Sh5QpUOSYiSzLzMJBSzGPnPsdz569GigdlrhMMM2g46hVnr6ftUm\nhd6qbQrsUGIBpaVq2bIlP//8M+CUWYEmCnW98sorAafYSkDx+OOPA27FUllZ6Y2vP0Q0Uf9S9iuT\nNxmGUfoU/Aik9u607+aPpJk5c6Y3M2om1LGxTp06ATVH7MApsj9VqihGjVy/59kfCda6dWsv/YwO\nTiiNkA5WKNQxnce3GMcfg6J0wVLmfB2kyJQ6dep4bZAy6/5SOSClQVK6X3ngZVN/8MEH3upQaq5w\nTa0qFU2mZICy2aXIuk8ysZkz7lson2IYRtEpmM2s68g+lOdW8dbaKx4xYoQ3u/m92JpRlQxeXuFc\nCMtmlqrqcIQOGMjTLk/osGHDvCN2Onqng+5K6i8V03FKv9oH2XcO02bWyidd9FaidikmWaupbHZA\nUlwv0D6zf3XgT1ivsbrqqqsA57vRPbvtttt6961eU8EGrcA6dOgAuHRBUmR9tvqdTSGDZJgyG0ZE\nCN2A0Yzrn501QylVjuxhRT/FHgnzexvvvPPOuM8OQ5GzJZkqdu7cGXBx1uqn9he1Bz58+HBOPvlk\nwPVDBeH02VJk4b9WMXwB4BRZ+7BaIQm1a8qUKV6cuX+/XRTa3o8dt+bNmwPuntPvZN+qCIF+L0+1\nfB1Tp071jrgeeuihgCtho1WWEjhKkXW/+9NEh4kps2FEhLzbzJqBlBJHNoMOr8sOkzd74sSJXmSU\nomj8pV/CJFebeerUqYCLKVeyPq04lARO53a///57LwpIZWdkb6Ur7ZkNYdjM/vZorJS0UOfPY9VP\n/6/VVTZpkAO0L6vkBPJOK8WPii8okaJS/eje1Tn0tdde29uVUWnXL7/8EnDnBfS3+q5kS2ejyGYz\nG0aZUXBvtuxEnVmWvagzvs2aNfNsmqAJ7FSsXGqYYbtyUmbN9IoS0rlWJYb/+OOPAbxY3s6dO3Pg\ngQcCbg9WiePSoYL0mb4fwvVmawy1pyrbUug7kAcfnDLl00bOZAxTec/1OxUd0Kk8nXDSCiQ21VGy\nsjOys2Pa5v0NOOUO4vcp2bRBMZ8F1F7CbbPNNt6yphCEHc6pwANV6tCgaRC/+uorb0sqVe3gsMhH\nOKceCAW76KCIthT/+OOPvByoSEa+a2wL9btt27Z88MEHQO3Jyh/AFIbJZMtswygzSu6gRaEp9EGL\nQlOshH6FJCxTKebzUr6vsrLSOz6p1/xKnEtCCT+mzIZRZpgymzL/6cl3gokw1LVly5ZAzdZkUEyZ\nDaPMMGU2Zf7TU25jmAxTZsOICIGU2TCM0sWU2TAigj3MhhER7GE2jIhgD7NhRAR7mA0jItjDbBgR\nwR5mw4gI9jAbRkSwh9kwIoI9zIYREf4fWhicUwhbcDIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1a3aa1ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1000, D: 0.2519, G:0.5202\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197285f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1250, D: 0.1873, G:0.1615\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztnXm0FMX1xz+PRcCIgKCERXABgYCKSoLCQQFXoiACJoYE\nlxwNYmIUJEZIjD+FJGrgqBi3BI8iEneRYFjcJW4EI+ASxBNFRTZlXwQC+n5/PL/TMz3Ts/Yyr+d+\nzuE83ixdVa+76lv31q1bVdXV1RiGUfupE3UFDMPwB+vMhhETrDMbRkywzmwYMcE6s2HEBOvMhhET\nrDMbRkywzmwYMcE6s2HEhHqFfLiqqip24WLV1dVV+n/c2wfxb2Pc25cNU2bDiAnWmQ0jJlhnLkPm\nz5/P/Pnzo66GUcuwzmwYMaGqkC2QcXcuxL19EP82xr192TBlNoyYUNDSVBhUV1dTVZXXQBRbevXq\nBcDtt98OwHHHHRdldQKlbt26AHz11VcR1ySdHTt2APCtb30LqHk2AXbt2sXRRx8NwMcffwzA3r17\nAfj6668BaNasGQCbNm0Krb5l15kbNWrEtm3bANhvv/0AEp1bf8ClS5dGUzmfqFOnZkKkGy9+8IMf\nADB37lwAjjnmmHArFgHNmzcH4PPPP4+4Juk0atQo5fe2bdsC0K9fPz744AMAPvzwQwAOP/xwAFq0\naAHAW2+9BUC7du1CqSvYNNswYkNoytyvXz8AXnzxxYzv79mzB4Bx48YlFFlImWu7Igu3IotHH30U\ngIULFwKOgseZclJkPWeaTuvvr58yCWbMmMHixYsB6NatW8o1unbtCsCGDRsAaNy4MUBitummW7du\nvPvuu77UP/5Pi2FUCKEtTfXu3RuAV199NeX1AssvtnhPoljWqF+/PuDMRtQuKYCcKbt37wbggAMO\nAODLL78suKxyWZpy+wmWL18OOMqmv0UxBHUPe/ToAcD3v/99AG644Qagpq716tVTeSnf0cyzb9++\nAGzevBlwHGKZuPbaawGYMGFCxvdtacowKozQbOZXXnkl78/uv//+AGzduhVwPIX6XTblqaee6mcV\nA2X27NkADBw4kKuvvhqAiRMnAo5auZW5YcOGgDN7KfclO9WzY8eObNy4EXBsRzfDhw8HHEXWd/v3\n7w94+1bCYNq0aQBceOGFQM1SFMDIkSOBGq/2zp07M3734IMPTvk9myILL0UuFFNmw4gJgdvMur7s\nvoMOOgiA999/36uMNPvarUx+KlWx9pa7LkOHDgXgiSeeyPh5je6NGjVKKLGu4b5W9+7dARIe0xNO\nOAGAN954I9/qJfDDZlbQhGx9zZCaNGkCOMEVsvHr1q2bCAJR29R+zTauueYaAA488EAALr74YsB5\nPnStfCjVZtbqyfbt21NeVxs0U2rQoEG2OgDOTEN/qz59+gCFzUwzXNtsZsOoJELfaDF58mQAxowZ\nk/J68sidS3HLQZlFrnDE1q1bA7Bu3TqgZpSXzTx69GgAbrzxRgCmTJmS8Rpt2rQBYNWqVQCsX78e\ncKKNsuGHMt9zzz2AY//+7ne/A2D16tWAo66alQwdOpQHH3wQcNr23nvvZby27uE+++yj+gIk1l6P\nOOKInPULypvtnjHlg55jqbjfz2g2TJkNIyaEpsyyKR9//HHA8dyq/OR6eI1m7rqWgzK77S0pdZcu\nXQB455130r5TaL1lh0m93DZ3NkpRZl3/hRdeABxPs9RHqF6fffYZUDNLOeSQQ/ItBoD//e9/gBOr\nrfVZ/T2zUU5bIN3PqPwK8jMUeU1TZsOoJCJLTvDMM88AzlqxtvtdfvnlCe+pvKRupEz5jNq5KHRU\n19rj/fffn/K6lEUqpQghvb527VoAWrVqlVNR3baa7C9dS+1//fXXE9slvShGmVV3+QFUD/d6uOIB\nDj30UMCJna9Tp45n/Lm7jH333RdwYpePPPJIAJYsWQLU3ONcz2iUypyrbu4ZaJFlmDIbRiURujLn\nsnvzqY/WrP3Y+F3oqK76SqEvuugiAE488cSUz7322muAo+D/93//Bzje7WxozXXq1KlAjZqDszav\nfbaaBWSjFJtZa70qR171l156CXA8zueddx7gzBzyYeXKlYATMbVixQoAHnnkEQB++ctfAjU2Z664\n7bCV+dhjj00kXJQn3+u5DdObHXpnVuPcThw9CFpsz/SdIMIaC30QND2cMWMGAMOGDQP8mfJrI4Wm\nr3qINRBo6WfZsmVAzRROU2GvaW0xnVlOKHVabYbQ390ryMJVjsp31wdwtj7qGrrmiBEjAHj22WeB\nmi2FubYIhtWZFTwC6ffb3V49z9kCTfLFptmGUWGUZXZOrzq5t9FFsTSlus2ZMweA888/H4CmTZsC\nThqZQnC36+233wYcZbziiisA2LJlC+Ao+HvvvZdYLsqynFewMi9atAhwNrho08PZZ58NQPv27QEn\niCUfNIMYN24cAFdddRXgTN2leprpaIPC1KlTE0te+qybsJT5iy++AGrUVkkHcmFBI4ZhFEzkylyM\nyz5Km1nhqFKW6667DoDrr7++5Loo5FP2mGxX8eSTTwJOAE4+lOIAO/bYYwF48803U8rVBhjZvYVk\n2PSyoRUqKodSIQStzMU8o3feeSdQs9QK3j6NPMs3ZTaMSiIyZVa5+YzqQW7KL3RUd9u38r5Onz4d\ncLyXhWzhCxI/wjndmwcWLFgApC/HZUJhncovrXRBnTp1yrcaOQlKmb36xs6dOxPLg1pZ0LZVebG9\n0ikXWQ9TZsOoJCJLgp9NbYvZehYWCj+dN28ekB6+WYgiuwMnhEZ9ea319zjssMMA+Oijj4qqe6Eo\ngZ0UWWqTjyILJYvX36lz584p75dTSiRthtAscdKkSQCMHTs25XP77rtvor533HEHkB4wI0VWwM+a\nNWsCqrWDKbNhxITQbWYvWyK5HkotI1utnGzmDN/P+LpXnb/++us0FXdHvXmplTYlFJJy14/kBAqf\nledeSuUVZlldXZ1InKAEBu5IKKlfFJtl3Oh508Yer8MHdL8aNGiQdwINpUe66aabUt7XM5AcVZbl\nWmYzG0YlEbrNLEVWcL6SFSTbyVLkBx54IOzq5cQ9osqz27NnT8BZg/3DH/4AwPjx49O+f9ZZZwFO\ngj63ErtHfSlFMUnw/UBpcxWJlouJEycmvLuy/7Uur3V6PxTZL/S8qU5es63kVEBeqzDaeOO1gUiv\n56PIhWLKbBgxIfIIMI12yaloZJso3tmdcDzKCDAvlPTuggsuABw7WCN3sl2shHja6qi12CC892Ee\nT6NZ144dOxKxy4ph1xEvQeD3OrMO8NMqg47WVRrg5BRAeka1HfePf/wjkD4jcyevKASzmQ2jwohc\nmd1kq497L7QfR56WOqq7Y7Pd9c+nrvrMSSedBJSWMN1NEMosO/ihhx4CYPDgwYCzq+ree+9N+BaU\nUkh7tD/55JNSi0/Db2XWc6b0Vdn2bQsp75AhQwBnp5lWILTjqhhMmQ2jwohcmTUKai1TCd6T0ciY\n7x7SQvB7VJcPQGllpLbJtlQ+mTr8IgybWamR5MkNO3IvyoR+YcTil23aoAzXBDIHpIcR4ldOOZeD\noFzOZw6SSruHXtg02zBiQmQbLUQ5Bdq7KSZ80jCiwpTZMGJC5MpczpgiF4+CZHLlvDb8w5TZMGKC\nKbMRCKbI4WPKbBgxoaB1ZsMwyhdTZsOICdaZDSMmFOQAi3uoXNzbB/FvY9zblw1TZsOICdaZDSMm\nWGc2QqVt27a0bds26mrEEuvMhhETIt/PHDWV5jwJu41KvaME80FQaffQC1Nmw4gJFpttBIqXImtG\n2KZNG8A5xiYu6HieTGmwgsKm2RU2RSuXNrrPbS6FKO9hGCeW2jTbMCoMU2ZT5lpPpd1DL0yZDSMm\nBN6Z69evn3b+cKlUVVWVTQLAESNGMGLEiJKuUa9evcQJEHFhz549eSUoGDduHOPGjQuhRv7StWtX\nunbtGnU1UjBlNoyYUDY2s9R7/PjxTJgwAXDOsJUKP/bYYwD88Ic/BPzxIBZrb6lOOnfppZdeAqBL\nly4AiVMrdOKBTrKsU6eOpwdUv7tPkCyFKGzmvXv3Js4v1oxDv+tMJjeleIXDtpkvuugiOnbsCMCv\nf/1rAF5++WUATj75ZNXJt/LMZjaMCiMwQ01nR8mevOuuuwDnGJpLLrkEqDkxEBzlqlu3bppCyfa6\n7bbbAPjoo48A54TBMJHC6FS/Zs2aZf28+wyiqqqqRPt0TvMNN9wAwNNPPw2kz0hqC5qd1KtXL3Hq\npe53rjbVhvRVeh7vu+++tMMb9LvX62FgymwYMSFwm3nNmjUATJkyBXBOQ9Qp9CtWrAAclZo0aVKm\ncjP+HqXNnPT9lN91DvHmzZsBePDBBwG44IIL0j6v/7vPbv7HP/4BwJlnnllodTLVL3Cb2f032LNn\nTyLCSwcJ6O8RBEHbzI8++igAQ4cOBTKftR3kLMpsZsOoMAJf3LzssssAmDlzJuCMYLI5dThb06ZN\nAVi4cCEPP/wwALfeemvKtaKwQ7xwj8T77LMPAKeffjrg2NY9e/ZM+678A2q70Hf8UOQgkTKde+65\nGd9v2LBhxiN6AT799FMA2rVrF0zlAsDdzq+++or+/fsDsGDBgiiqlBFTZsOICYHbzG4Fc5fXunVr\nwNkCt23bNho3blxoMUVTqr0lG3nr1q15fX7ZsmWJtegwCNJmlofavabcvn37xIqD2LZtG+D4SjQ7\n8YOgbeZMqytqs/CaifhUvtnMhlFJBG4zu5XY7Ql0b0rPpspSeV3DjwipUslXkUU2VVa0mBRg+/bt\nxVcsQPr27QuQpk5SanDulT6jiLgZM2YAMGTIkKCrWTKnnHIK4DyTet7++9//JmYhimg77LDDANJm\nJGFSNuGcyaxduxaAb3/72ymv62FRCKUfJw1GsX1u0KBBAPz9739PeV1TT7XPD4KYZmtKmc9yjO7Z\nli1bAGjevDngLFkpR1gpBHUP1WHVhsmTJwM192fUqFGAMzi///77qovq4Vc1bJptGJVG5MqsaVjy\nlHnAgAEAvPbaa4ATcCDF0ojpxzQ0CmVu2LAh4MwsNPKPHz8ecAJr/MBPZda9Uoiqe5qdD26180PB\ngr6HCmjS8/jcc88l6q97qHuq9nTv3h2AJUuWlFy+KbNhVBiRK7M2ZMimAmfzQqdOnQB49dVXAcce\n6d27NwCLFy8GSlvmCHpU10h91FFHAbB06dKET6Bly5YpnwnD3vKjjQoAku0vh+ScOXMA6NevH3Pn\nzgUcR5ccRQquEcuXLwccm3Pw4MEF1yfoeyj1lYOyqqoq4QR88sknAeeZ1QxTQVAKDFJYczGYMhtG\nhRF5rpqNGzemvaZcw7fccgvgKHNt2xIIjtpKjcFRZPfSWm1pn3uDiH5mmuVpxtWkSZOU1xX2On/+\n/MDq6ReZ0l49//zzAEydOhXw9vAnzziDxpTZMGJC5DazkI2xdevWxCingBKFfLrxI5F6WN5sBR5s\n2LAhYTcGYSO7CTNtkGYayV5udxtnz54NwMCBAzO+Xwxh3cOTTjoJcFIEfVO2ys34nTPOOAOAefPm\nFV2u2cyGUWGUjTKL3bt3J84fevvtt4F0ZZYHPJO9XShhrzNXV1fz2WefASTOKa4tyiyP7NixYwEn\nNDNDmYk2aT3WnUrYz1mJ3/fQnfLIzcqVKxOrE3oG3e3o168fAC+++GKp1TFlNoxKI3JvtpuGDRty\n+OGHA962sh+KHBVffvllKIocBK1atQKcxAJeZy9XVVUxbNgwwFHkzp07A856cjm33e2Zds9eDznk\nkERSAq92+KHIhWLKbBgxoWxsZsW2Llq0iCOPPFLlAc7I2KFDB6BmCxqkx/kWQ1g284cffgjUbJVz\nj+ZKGHfiiScC6bvFSiFIb3Y+W1LD9tgHeQ+1N+D555+nV69eAIlZ5MqVKwEn4svPBIZmMxtGhVE2\nyiyGDh2a2MguhVIssNaTpQB+H98SljfbvW9ZqqWfalemlK5FlBfJka6KeNMhB9oRFoRCh30Pe/fu\nnYgVmDVrFlAzowTneBo/MWU2jAojcmXOFCFz8803A3D11VenfFajoXbg5FoPzIegR3Vl1JAt1bhx\n47RUQ1o337RpU8rr+o6uUQx22How3H333QBceumlgZeVrzJH3pkzccQRRwDwwQcfBF5WWA+CAiwe\nf/zxxLY5rylnUCd2fHNt68y1DJtmG0aFUTbK7MeUuRiCGtXd6qqAi02bNiU2iCiAIkhMmWs/psyG\nUWGUjTInc+qppwLw7LPPBl5WFKP6hg0bACftbJCYMtd+TJkNo8IoS2UOk0ob1ePexri3LxumzIYR\nEwpSZsMwyhdTZsOICdaZDSMmFJRpJO7Ohbi3D+Lfxri3LxumzIYRE6wzG0ZMsM5sGDHBOrNhxATr\nzIYRE6wzG0ZMsM5s+EaHDh0S6ZBzUV1d7UsmlTCpW7duyqF45YZttKiwNcpyaaP73GolbyjyWpHd\nQ69TPfzE1pkNo8Iou7OmjHjTo0ePlN91OkltJUhFLhRTZsOICbXCZpZdpRMuHnvsMQDOPffckq9d\nrL2llD86kVLnXclB8vnnnwNw4IEHAnDccccB8NZbbyWuoaR/u3btAqBBgwaAv8kNy81m9nresp10\noRNOtm/f7nXN0G1m97lnQWI2s2FUGKEpszv1rH4uW7YMgC5dunh+1gudyeReLijkPKNCRvXmzZsn\nkvG5z4UqpMx82zdgwAAAnnjiCQCuvPJKAP7617/mXVZUyqy25VJVKZz7HLECywpVmceOHcvEiRMB\nZzal9vpxPpgbU2bDqDACV2Zd/7vf/S7gnJbnxdq1a2nZsiXgjHL51lGjus5tzrN+BY3qs2fPBkic\nFzV8+PC8y3LjPjvLPdPQ8Tw6rmf58uUAdO7cOe8ywlDmfGz8XPewlNMhg1bmTDMp973Se9OmTQNg\n6tSpALzyyisll2/KbBgVRmjKLKRCUiXxzDPPAHDaaaflHKXd19Ro+PLLLwNw3333FVK/gkZ1ncyo\nM5ZzeZz1fvIIXmj7xH/+8x8AunbtmquaydeK1Jvt1ZbNmzcD0KxZMz/KCMVm/u1vfwvAhAkT0t77\n4osvAKc99evX961cU2bDqDACU+bjjz8egOnTpwPQpk0bABo1auR1bQBWr15N69atM34mV12l9rJn\n8lmnLXZU1wzDawTu06cPAAsWLABS7X8vZc7VvlNOOQWAESNGAHDhhRfmrGe5KnMpNnKGMkJRZj1X\nderUSZzP/LOf/Qxwnms9F35iymwYFUZgsdlS5o4dOwIwa9YsAM4++2wAunXrBsC7776b8j0vVQbv\n9Vk/R/l8kQ2ssp9//nkATj755JTX3euO2eqqo1615ur+jtZsX3/99RJqHg7aTeRGEVOaNQWxLus3\n+nsn+z0uvfTSlM8oii/K9pT/X9IwjLwIzGZWrLJGKtmze/bs0bXyLle46yoV1zXXr19fzDWLsrc0\nEstmViSQn+277LLLAGfNUtdWmV999VVOv0DUNrNQNNs999wDQLt27Xy7dtgRYHfffTcjR44E4KCD\nDgLghRdeAODII4/0vbx8bebQlqb0cOcTyqhNCf/+978zXiupPoVWJ1P9CnoQNChpsNqyZQsAjRs3\n9qMuKb/73b5vrhn4w57p3ro3lTRs2NDP8kLpzHJyffnll2nvqX27d+8GnMHdD8wBZhgVRuDJCTTN\nzndzAcCaNWtSfnd/5/LLL/epdoWjaa1+Nm3atOBruMMf3e0rJChEoauaKUTJqlWrABg4cGAi7FX3\nXSaRn4ocNrovVVVVaffMPQONAlNmw4gJgdnMn3zyCeCMWFp2yXBNwAmEeOihh3IuvLudaaVQrL01\nZcoUAEaPHg14b93TcsZzzz0HwKmnnpqz3kEFVHxzbd9tymzPUBhKFbTNnE8fUTtvvPFGAK655ho/\nyzeb2TAqicC92Qo837Rpk64BpI928hTu2rUr53JLOYUC5usLUHqhfDYW1DZl1kxD9nudOnUS9zAO\nyiySA120TXfdunVBFZfAlNkwKoyyS+hXXV2dSDGj8MUgR/ewRnXZzpm8zkOGDAFg5syZvpdbijJr\nq9+1116b9XPyzstvsGzZMr7zne8UVtEsNGnSBHDW9N2EdQ8zeazdySYDKteU2TAqibJU5gzlBlle\nqKGAUbbvm7KKbuO9994LwE9/+lNdS2WkfbbUNim9lNJNZcPve3jBBRcATtILkTy7Uvu0CeOEE04o\ntVhPTJkNo8Ioa2WOkydUbUn21K9YsQKAww47LKhiA/Fm6x65N34klVFqEYXWJ5B76E7hnBxLIJ+A\nUjkFiSmzYVQYZaPMmRQ5jHjXsD2h35QDOMqs6Dc/0rJmKNc3Zd5///0B6NevHwBPPfUU4HiZi4lT\n94NyOJZX6aF0b5U2yg9MmQ2jwigbZZbdlRyXHSeb+YorrgDg1ltvTbym1Dru/bHyol588cVAaTHo\nQdrMsv+V4rh///6lXrrY+oSuzFr7Vspg3SN3Cmk/MGU2jAoj8sPWt23bBjjHvUS5H9RP3njjDQB6\n9uwJOEe5tm3blmHDhgHw4YcfAtCqVauU72qdU/zrX/8C4Hvf+15wFS4Ct7e3kpAiK+XuqFGjoqwO\nEOI0O9cmejlRNH0JC7+maF7t0yb9s846C6g5m2rGjBlA+jlF4kc/+hFQsx20VMolB1iQRDHNPu+8\n8wB4+OGHAy/LptmGUWFE5gBTuccccwwAixcvVhl+FZFvPXwZ1b3On5ZSS7mrq6u56qqrALj99tsB\nJxjBfS+uv/56AK677rpiq2XKHANMmQ2jwiibpalkwkyOFtSo7j572VWmyvOrOE+CUOZCkjOGgSlz\nDabMhhETIl+aykQclqeyJSWs7e0rF0U2UjFlNoyYUJDNbBhG+WLKbBgxwTqzYcSEghxgcXf7x719\nEP82xr192TBlNoyYYJ3ZMGKCdWYjVAYPHszgwYOjrkYssc5sGDGhLGOzw6TSnCdxb2Pc25cNU2bD\niAnWmcuQXbt2sWvXrqirEQpVVVW1LlbdnfS/XLBpdoVN0eLexrDbF8Z2UJtmG0aFEdoWyBdffBFw\nTkMwjNpM3759AXjppZcirUcypsyGERN8t5k3bdoEQLNmzYB0W8J90nw+zg93mh0lwPMjb3MU9ta8\nefMAOOOMMwIvy2xmbxo2bAiQ09moRBM6gWTPnj3885//BOCSSy4B4OOPP87rWsVgNrNhVBiBebMz\nnUec7XPZToH0ok6dOillFLPEEbYyb9u2jf322w9wTlGcMmUK4PgV/CRMZT7++OMBWLhwYdq9+/nP\nfw7AHXfc4Xu5xd5D93PWoEEDAC6//HIA/vSnPwHOwQw6qCHTd8Xf/vY3wDn0wI9DHUyZDaPCCMyb\nnUuRhXtkmzRpUuI12R+ybdyj4WeffZby3U6dOgGwfPnyImsdHJ07dwagcePGCZv5nHPOAcJNvesn\nv/nNbwD4/e9/D8DTTz8NQIsWLdI+++c//xnwVuYw0/eqLPlcdArnO++8A8CPf/xjwDmEQIo8Z84c\nAB555JG02aDqvWbNGsA5y7px48aAc6ZakJgyG0ZMCMxmzve6GuGSD1HTKKbRzeva+o682xnqm089\nA7WZM/0dNOO45ZZbABg/frzfxSaXH5jNPHfuXABOP/10wDnJs2nTpgn7c/v27UCwIZCl3kN5q3WE\nkHwxXmvJ1dXViWdL7dL5zG5fkR+zLbOZDaPC8N1mln2bLxoFk/FSZDFkyBAApk+fXlBZYeI1Il95\n5ZXcdtttGd876qijAHj77bcDq5cfqG2DBg0CHGVr2rRp4jO7d+8G0hVZdqna6jWDC9OG1lFC7rLd\nijxy5MjE/5955hkATjvttJTPaEVizJgxQLpyB4kps2HEBN9t5lzX06gnm0ojeCGsX78egAULFgBw\n4oknAnDAAQeklBGlzawIuI0bNwLO6D9t2jSGDx+e8lnZZmpPvisB+eCnzeynZ9ZP5Q3a7+FW1x07\ndnDQQQepbMDxiO/YsQOARo0aAc5zXooym81sGBWG78qseGN5OrNcK+9y3ajOss+1Dij7O9lOy1WO\n36O6RmJ3jO4DDzwAwPnnn5/wwkuB1R6N5n7G9/qhzFo33rBhg64JOPda6819+vQBalYZvFYYhg0b\nBjhrtlI0t1K7o/uyUQ570vXMyX/gXqUphXyVObRptk8u+qzvq1P36NEDgNdeey0RSKINIBmu6euD\n8Ktf/QqACRMmAM60SyZAMgp6OfroowGns7Rr1w6AlStXllqdkjrziBEjADj22GMBGD16NAB79+4F\n4OCDDwZg2bJlgGMmDBo0yDMQRq/rGuoEpUy7o+jMGqxuvvlmwFleVCeWWeWH48um2YZRYYSmzK+8\n8grgTMWKQdfW6KflgQEDBgDw3nvvAdChQwegRvGkGl4zA79HdZW9ePFigMSmCtGuXTs+/fTTjN9V\nHeUU1JS9FEpRZqnLTTfdBMAvfvELALp16wbA+++/71Vm3jMxr8+1bNkSgHXr1uVU7SiUedy4cYAT\npqqAGc0OmzdvDngHNBWCKbNhVBiBhXPOnj0bcLaC+Wkzu0dqjYJaBirwmr6O6nJi7dy5M6WOchaN\nGTMmsVVQwTFymriDF5K3FBZLKcosW/nNN98EYNWqVQC0bdsWcGzlLl26lFI/ABYtWgRAz549i7lG\noMqsOt1///1ATXvd/ebOO+8E4LLLLlM9fCvflNkwKozAU+2uWLECgEMPPbTQr6YhBZbX1w+CGtXz\n2dYoj64C/JPqkXKNEutRtDIvWbIEcLaWatbh3kTgtVUVYPXq1QC0adMm5buTJ08GYOzYsfk3xoOw\nbObu3bsD8O6776Z5qffdd1/AmZH5iSmzYVQYgafaLUWR3Vsc3YrsVj8vpYsCtyIrBFIhkZAeUKCE\ncVqb9tOrXQxSIpUvVX3iiScAOPfcc1M+n2kmMWrUqIzv/eUvf0l5vTYkZlD79+zZkwiK0kpKMWHJ\nfmPKbBgxIXoJc5G8RqmQPvdanUZId1RVOSmyW4mkyMntc39GiqyfUSmyG6nO0qVLAbjuuusyfi65\nXfr/rFk+A7PJAAACCklEQVSzUj4jj708+H7YzH7jdX+St+tKkcsJU2bDiAlld3Dc7t2707ymuSjF\n7go7eqiqqooXXngBCOeonnJJgi9vrzZWCM2m5O8ohrDvYXKfkR8nUxJDH8szb7ZhVBJlo8yZkuBn\nei/590KSEGQpN7Ltc2F4cstFmYWUWUrdq1cvoGaHW7GEdQ+zHdSwefNmwElK4XO5psyGUUmE7v5V\n5I8SnimWNRm3ErvXaGvDmmQ2fvKTnwAwceJEoHattRaL4sy1q0yUoshhk6zGumdh2Mz5YspsGHFB\no0w+/4Bqv/55ceaZZ3q+l+saRdYjkPaVy78g72Ex/1atWlW9atWqxO+jRo2qHjVqlG9t9LOuVVVV\n1VVVVdVbt26t3rp1a+L1p556ypdnr9h76PUvcgeYAkJ0vm2LFi0SebGfe+45d/kAvk5Lo3SAhUG5\nOcCCIGwH2DnnnMPMmTNVXlDFJZdrDjDDqCQij3/UZgOl19mxY0diy53XqKfXpeaHHHJIsJU0AqOQ\nLJxho00id911F+AkWmzfvn1iaa2cMGU2jJgQuc2ciTCXasxmrv0EdQ+znTKqdFg6kzpIzGY2jAqj\nLJU5TEyZaz+Vdg+9MGU2jJhQkDIbhlG+mDIbRkywzmwYMcE6s2HEBOvMhhETrDMbRkywzmwYMcE6\ns2HEBOvMhhETrDMbRkywzmwYMeH/AWxKQ6UjImDWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19713ded0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1500, D: 0.2349, G:0.1759\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nxPmuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1969f8b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1750, D: 0.2361, G:0.1633\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nPMEeZsPIE/4fWOTi5+W6O54AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19745e790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 2000, D: 0.2453, G:0.1532\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfy7WD17I9o33AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1977ffdd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 2250, D: 0.2494, G:0.138\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197ee9a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 2500, D: 0.2395, G:0.1386\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIybYw2wYMeH/ASxfLydq3bzuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19782d350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 2750, D: 0.244, G:0.1394\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1975a3dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 3000, D: 0.2525, G:0.1413\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1971eaa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 3250, D: 0.241, G:0.1506\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ns2GUCf8PYia8RfpcHTIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1972c7550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 3500, D: 0.2368, G:0.1453\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztnXm8VeMax78nciINKilFGigUmcocboRMZS5Fl4zJPIQy\nFXG7ZCYRURkiohCuSFKmImQqhEJFbtLtqO4f5/Nb797r7Hmvtfdu7+f7z6kzrLXetfZ6f+8zvM9T\ntm7dOgzDWP+plu8LMAwjGOxlNowiwV5mwygS7GU2jCLBXmbDKBLsZTaMIsFeZsMoEuxlNowiwV5m\nwygSNkznl8vKyoouXWzdunVl+nexjw+Kf4zFPr5EmDIbRpFgL7NhFAn2MhtGkWAvs2EUCWk5wAzD\nqKSsLNonVQhbiU2ZDaNIyJkyX3PNNQAMHjw46vsbbLABAGvWrMn6HF9//TUArVq1yvpYhcAJJ5wA\nwFNPPQVAhw4dAJg1a1ZOr6NevXoAfPXVVwCMGDECgLlz5wKwbNkyAF577TUAKioqcnp9+WC//fYD\n4K233sr6WNdeey0A119/fVbHKUtneZBJDE/LkU022QSA4447DoBHH3006d926tQJgDfffBOA8vJy\nAH788ceo/2+66aZRf/fll18CsN1221G9enUA/v7775jnCCtGqfGuXLkSgCeeeAKAHj16VFmS6Rr/\n97//ATBu3DgAevXqBcDatWt1rWlfRzZxZt3XZ555BoBDDjkk6ufffvst4Cbkc845B4DzzjuPgw8+\nGIBq1SoXf02bNgVg0aJF6Q0gBYJ6hrVq1QLgv//9b9LfrVmzJuDG/scff2R6Wu8eCT1vYXFmwygx\nQlfmdIm8Hi3rpBBXX301AA8//HBKx3rttdc8hUhwvkCVeejQoQBcdtllOmbU10Roybb//vsD8MMP\nPwDwzjvvAPD4448DMHv2bAAWLlyY9JhBKLNfqaQcEyZMAODoo48GYMMN41tt48ePB+D4449P9fQp\nk88MsI033ljXAMCqVasCP4cps2GUGHlTZinX6NGjAVi8eHHSv5Ftodlwm222AeDTTz8F3Kx4wAEH\nADBz5sykx8x2Vtc11a5dG4Dffvst5b/95ptvADeOX375BXC+AK1Ehg8fDsBGG20Udc5UyESZpbC6\nn1Ji2fbZIF+Cjh1ESKcQc7P1rFavXp31sUyZDaPECF2Z44We9t13X8DZiYlsyhUrVgDQv39/AEaN\nGpXuZcQl3Vm9S5cuALzyyiuAC8fccccdAEycODHeeYBK9dU9kUo1aNAAcJ5vP7Jdf/rpJ8AppP4+\nEakq88477wzAHnvswQMPPADAZpttBsDy5csBuPjiiwG4+eabAReCkpJrXIkUfLfddgNgyZIlAHz/\n/fdJx5CMfCrzUUcdBcB//vMfoNKTD3DFFVcA0LJlSyDxik33TfezWbNmgPOJmDIbRokRetJIvGQQ\n2RKpeHm33nprID17NCykyOLII48E4tt+mqG1Eunatas39ho1agBOkWWbyiaeM2cOAFdddRUADRs2\nBFw8Okh0rjlz5nhx5bfffhtwMXopdpMmTQC3YjjzzDMBF2utXbu25wHX72hMSny5//77AadKW221\nFeBi16KsrKwgUiX96HOrnAetXoTGq4Qa3UMl2ujrnnvuSfPmzb1/Q2pRiliYMhtGkZCzdE7NwPrq\nV7hIFF+Vdzeb7Jqw0Mz7119/Ac6+9CN7WLYVuNWKZvcFCxYAzqstZMfqq9ROsewwaNCgAUuXLgXc\ns1I6p2y6rl27As7rLurUqQNA9+7duffeewHn5ZffQ5l/bdu2BdyKQPdEXuBUVmz5olq1at4zuPTS\nS4H416tV1IwZMwB3j0455RSgMgVZ9zXbNF1TZsMoEnKmzJp5f//9d6BqPnUkij0r0ymITRhBI/tW\nM7LseeWFt27dOur3I3O1J02aBLh4+Q477OD9LBLZioniylLHoOzoJUuWeN5pqeegQYMAtxFg+vTp\nAJx44omAyyGXHXzkkUeyxRZbxLxOrS6k+oo3K9tPFKKdvM8++wCV13zssccC7vl3794dgBdffBGo\nGsXRV3/edZCYMhtGkRB6nHnLLbcEXIxUXj3NXOKmm24CKj23UhkphLy4P//8MxBMJpIIKkapa9X4\n9H/N4Io/16lTh/nz5wPuHshOFLKh//nPfwIwderUTC8rowwwv/2nraVt2rQB4OOPPwacja/c8X/8\n4x8ADBkyxLMlNTZ9zvzHVnxWz7ZHjx7JB+Uj7Djz7rvvDjhfwYABA7zPpFZku+66K+D8PMpozGSF\noZVYxG45izMbRimR89xsKZTis6kge0vZNcpVXh/yeuWh3GOPPbzvaeXh9wZHXEdg589m15Ti4LJr\npcTye2hlIQ+t1Kh79+707NkTcBlzshn9O6u0SnnvvfcA+PXXXwE4//zzvXMk85mE/Qy1uoj0Syiu\nLG+9ducpo1HqGoQvI1VlzpkDTIPTB+HJJ58EXGrmEUccAcDll1/uhXs233xzAO6++24A+vbtCzhn\nkpZmI0eODP3600XVIyJfYhHvJS40p49/O5+SG+QAEwpliXHjxnnbNd9//30AWrRoATinnyYKfX/A\ngAGAe4k1oeXT+ankGaVkRqJCBnpmCj2paIEcfRpHLp6tLbMNo0gIfZktRR44cCDgaidp+TlkyBAA\n/vzzz7jHUNKIZkMhZ1M2DrGwlmhK2dQ2TKVzJiKMRIkg29MorVYpjPFUc4MNNqBdu3aACy9qlSUH\nkR+F5bRq0cqtd+/eeVtm6/P2wQcfAO7ztv3223uOXW3+UaqrVhzz5s0D3DI8XuLTxhtv7K1E42EO\nMMMoMUK3meVeP/TQQwGXaC83fyoOAv9WP83UUv3DDjsMgJdeegnIrZ3iR5sOGjduDLjxaWaOpb7Z\nJBIo2WLbbbfN+BjJkJ0rp0+y623SpIlXhDEy0QJg7NixgEtvlY2pZywFv/POO4HKZ60EI6WE5go9\nKymzrrm8vJzTTz8dgPvuuw9wSUIKtamAoVYx8bYCJ1PldDBlNowiIWfe7HvuuQeAjh07Ak6p4nl2\nI/GHMzSbSTGk0P7Z7/nnn/eKzYWN1EorDnnYjznmmCq/K4XRuDQO/7HipXFqu+Bvv/0WqiL7yxQr\nOURb9V599VXAFSBUiKphw4be5hAlkjz00EMA9OnTB3ArFtnQsk+1/a9Ro0ZApVfY7ysJG60SdJ91\nH5QA9Pfff3s2vXw9KoOlrY2nnXYaALfccgvgNqn4E0KCxJTZMIqE0L3ZmtV23HFHwHn5silJ+vnn\nnwNO4WSHK0FBWyg1SyYiKE+o1EubJr744ou4v1u/fn3AbVyX3SiPru5ZvGJw6fgEgkgaueSSS6K+\nyoOr8yvurJTd2rVre6sOJZJoTMoZkM2pe6Cf161bF0gvUpHtM9T9V6cOlUfSM5T/QyvCDh06eOmq\n8tfoXsg39O677+p6gOzi5ebNNowSIxBlTsXb+MILLwDOI3jllVcCrjhcIvr16wfAI488ArjeS0oJ\n1UYAZShlqlzZxNFTbSHTuXNnXn/99YS/0759e8D5FdTSRcpwxhlnAKllvgURZ5ZnVsUL5alWcT6t\nNJTuWatWLc+WlELLy6sNCVK9XXbZJepc2kKoz0mYz1ApmJMnT466VqHVowpMyFfQt29f73nLO6/P\nsVaJspGlyNlEVkyZDaPEyFsRfG0di1Vu5/LLLwdcDC9e9oxmPSmWsm3SGVNQNrO88vF8AcpB17bG\nWKgYgLzEshuVPTZs2DDAKeWYMWM8GzQeQSizvO3KhdfGA//WTeUyT5482fNen3vuuYBTLnm8/Vx4\n4YWAiy9HXG/S55npM5TnXPczxnEBZwfLM3/llVd6KzK/xz9eg8JsMGU2jBIjcGWOF0dTrFB2tTzN\nahOqn0+dOrVKyZl4SBmy6QcclDJrs7qKuvvj57LHYnk19QxkR/pLDqn4m2w3FUNctWpVldK0MY4d\nWG622uXI2yvPs39L56uvvurtFlO5Xqm7xi+Vu/322wG3y0ykE+3I9hnKn6NtmBdccAHgivVpp98n\nn3wCVLYVShZxCBJTZsMoMXLWbF22RDpNz5KhLCHZcpmQ7ayujCbt39UqQaoVq3D/4MGDAbjmmmvi\nXZOuB3CxWq1YdI5UsueCUGZ5qbXqUKaddkTpOUih69at6xX3u+iiiwC3IlPkQ4qmuLya6GVCWLum\n/FGafOX8mzIbRokRmjIra0YZX8qyyaY9qN/ujCwCmClBzepacWifq5RHZXBSycXVXm/lWwfRIC9I\nm9mPfBby0Ct3e/bs2VUynxRx2GuvvQDnSZbq6XOYSc5yps/QX4SxUElVmUNfZiv0pIf54YcfAu7l\n1oZ3MXLkSG8bYarXlk3yeqYfBDmltLyOx/PPPw9Ed7Two8T+ILfDiTBfZqHSP9OmTQMqn4MmNXW2\nkDNJS3H/klVldjLZVFGI/ZmDxJbZhlFi5C1ppFAotVk9F2NMlOghp52WtkEU7EvlGYa59TBsTJkN\no8TIWXECo3RItNoLo7d0KqyPipwupsyGUSTYy2wYRYK9zIZRJKTlzTYMo3AxZTaMIsFeZsMoEtIK\nTRV7UkUY41OHBuVo55p8JI3kmlJL/ImHZYCV2Aeh2MdY7ONLhC2zDaNIsJc5j5SVlYXSxtUoTexl\nNowiwXKz84jF+I0gMWU2jCLBXuYsCcLuNdu5MFi3bt16vVoq6GW2akxdd911gOtXpJ5HhYAe/pdf\nfgm4mteJPhSqXKnSSUuXLgVcV4dS4oQTTgDw+h1rUvP32s4lN9xwQ9RXf7+ounXrVqm6qp+pV7Xq\nofl7kB1xxBEATJo0yft+UBO5KbNhFAl5TxrRrKSvjz32GAcddBDgsqc0S6vipbohzJo1K+r7mZBt\nwoF6FY8fPx5wNaY1M2tcEydOBCpnZt1zzfiqzxzGxv1CSRpRJUw9y08//RTA63yhsau8T6KOon7C\nThrp1q0b4IpPDh8+PONjSZnV7TIVVbakEcMoMXKuzLKDe/fuDcCECRMAV2f7rbfe8joF+mctf3nW\nvffeG3Bd6jOxszKd1dWpQbW7VaBOKqseyyoxe/TRRwPRpWRVdrhjx45RxwiSfChzixYtWLBgAeD6\ncL/xxhuA6z2lzp5DhgwBYM6cOQD89NNPgKu3nkq5n7CUWedOx6bV72rloR7WKkf82WefpX0dpsyG\nUWIEoszp9OBp1qwZ4HYRyUaS7dS+fXuOOeYYAPbZZx/AKa7wn2fcuHEA9OzZs8r5/DaKn1Rm9QED\nBgCVPYbV10rea12j+g+ru4ZUVgqjnkrVqlXzOlVIvWfOnAnAOeecE/MasyFdZa5fv77nXfcjdZHq\naEWhjp4q5l9WVsbKlSsBqFGjBgDLli0DXKldrb4WLVoEuC6ReraysWvVqsXy5ctTHmOQyqzzqu93\nLLQKVIeWTNQ8GabMhlFi5Mxm1kzVvHlzAK+vsJR58uTJQGXvX838wn+Nf/75J+BammgG3X777YH0\nyqqmO6urj7Dazey6664AHH744QC8/vrrgOvlu9VWWwHwxBNPAJXjVfzy7LPPBvDa8ahzZJAkU+ZE\nxeHr168PQJs2bYBKfwbgqa4YNGgQ4FoRXXTRRd7ffvfddwC0atUKcM9OnSwPO+wwoLKnM8APP/wA\nwPvvvw84T3KqYwxCmR966CHA9Wu+7777on7epk0br2ulVmBff/014MYp9DlXlCMTTJkNo8TIuTLL\nu6f4rDoIpuPJlW2mOLSyruTVlqc0FTKd1VetWgU4b/y///1vwM3Mt956a9Q1qrdx69atadu2LeA8\nuFJHf2fM+fPnRx1DdqVUL55tG298kNoYd955ZwAuuOACAE488UTA3XchW1mrE6ktuGjFU089Bbj7\nJaTuGlPE9QLp9fEOWpkbNGgAwC+//KJjAs7OHzlypHdPcpH+acpsGCVGznKzNYNJiUeMGAFkFluV\nbalY5uDBgwGYMmVK1teZDCmGxqNZW7aR4snKAFNeuX7euHFjz8PrVx8pmzykX3zxBeDscP2+PMNh\nIcX9/fffgaqKLNq1axf3GKNHj054DrXC7du3b9T3C2Gjw5IlS4CqHmn5ZsrKyjwbv3PnzjF/Nx+Y\nMhtGkRC6MmvG0kx97rnnAvGbbidqBypleuaZZ6KO4fc2hkm9evUA6NOnD+Bi3Gq+rt0/n3/+OVB1\n18yGG27oxVbjIftbWVOy4YSy6GrXrh141c/q1at7ue5aEfi54oorsj7PWWedBVRV5kJo8KZn6Ed2\nfqzPp/97+VBqU2bDKBJCV2Z5aE899VSgqq3p914mmpn1OzvttBMA/fr1A2C77bYDSKp4QSB7qnv3\n7oAbh7yy8RRZWWxjx471ssb8yDutc7z88stRP7/rrrsAOP/884HK7LOpU6cCzr7NloqKCm9f9b/+\n9a+YvyPvdSLiZQXq+/Gec9j+gFQ46aSTALfa+vHHHwEXVUgF/+c8F+R9C6RCOXIKPfDAA16igEID\nQhsr9PJqOfTXX39lfP50wxqaUBo2bAi4MJg/bdH/EJ977jmg8gXRh+LZZ58FnGNFmzJGjhwZ89xK\n//z444+9c2hjR7yUx3RDU3vvvTfTp09P9Cve2OMt8ROZSkquaNmyZdT3NSZN1JH3T/dl2LBhMY8Z\nVjqnUkrlpM3GOZfNS22hKcMoMfKmzP7tilKYRo0aealy/mtr1KgR4JahQWwZzHRWlzrpWpREIIeY\nP+yk/1dUVMSd6XUvpNz+Dfonn3wy4BIxdtllF29LpZxlfjJJGpFjUcrkH4scZBq7NmDo+idPnuyF\n6LRqGjp0KFDVeaZ0T23AkWkxZswYoDLNU5tb4lEIHS2SvUemzIZhpEzeCvr5HQTaOjh8+PC4s5wU\nTcn5L7zwQtiXGReFVnr06AHgqcdHH30EuK2PWoEcfPDBQOW4pXhKcdSG/AMPPDDq+0L3SKovNtlk\nEy9Rxp8Kmg2dOnUC4MEHHwRcKqo2k+j5KGQmx5wSglq2bOkprWzkJk2axDyXVjjaNKMCf1qp+f0m\nhUoyh1cuHGKmzIZRJOTdmx0LbaXT1kBtOJC66ftBkKm95d+Erv8rvU+e6ljbGqVCsne10tCWSBU0\nlPdadqXUV+mV48eP985z9913Jx1fumPU2PxlmPzqIhtfNjS4VYZCZ9o6qq8LFy4EnK2sFYwUWVGC\nZcuWJd0aWgg2s1A467HHHov6vtJ5tQU4HcxmNowSI282c6w0TqEC45rltGWwEJLZhcr8KoFCHl+l\nQMa71jVr1njqI5tfhRn8fyNvtr6vckry+Hbp0qVKSaUg0bNRDF0bQdSEQMXpYqXm+r3rUuSBAwcC\nLnasc8gfoni5ihOEUbAhTFQWyY8/bTUMTJkNo0jIuc0suy9RVo1afDz66KMA7LnnnoCzyfypktmQ\nqb11/PHHAy7jSx5olY5VyqY815Eo9qrrVyqoX5m33XZbAO68807AlSqKjK8nKy+c7yL48guMHTsW\ncEq7ePFiwN1HZX5J7dPJIUjlGWqTRLztnNmiccYrjGFxZsMwUiZwZU6mFMnK8m644YbeLKpjyXut\nErVBbpMLyhMqT7vizL169QKcrSi7s7y83LMx5ROQmitfWeqVTouWeORLmfXstClEBQ5feeUVoGp2\nmbLbVPgwF40MUjiujlnlZ6nmbeuzmo1vw5TZMEqMnNnMKoYme1GxSdlOsodr1qzp2dUqYK+WJsmK\noWdC2DFKzerKjnr00Uer2IOytxR/DpJ828yROengfAzKHpsxYwYA++23H5BZC9egnqE+m/JI+5sa\nZtOuJhtMmQ2jxAhNmadNmwY4O1A5uMovltdPLVkiZzApsFq3fvDBBylfY7oUUvaQf3eS2qJkU3gg\nl8qsFcaaNWvo0KEDULX0kH+MetbZxJODeoZhFBM0ZTYMI21Ct5nzVZ0hVQpBmTVOqZbsxnQa8sUj\nl8pcs2ZN79+y/1UdRrayygfLVpZfZMsttwRcmd90yPYZJitllIhHHnkEcK17FHEJklSVOfR0Trnk\n5VzQ//VVNzBy+aWui6WCxt60aVPAbTSZPXs24LYBylQpVNRHqry83Hu+mohUNkmfAyXV6Of5rP3l\n7zwZzwmnDiTq+FFo2DLbMIqEnIWmVOtZCSFKPH/44YcBF5qaO3eut30uFxTCMluoJreKA6iPVSJ0\nX1XKx0++Q1O5oJCeYRiYA8wwSoy8Fyfw15XOdUeDUpvVi32MxT6+RJgyG0aRkLfiBKKQCg4YxvqM\nKbNhFAlp2cyGYRQupsyGUSTYy2wYRUJaDrBcuf2DyElOlVILa4QxRrWirV+/ftCHTolSe4bxyHuc\nOd+U2geh2MdY7ONLhC2zDaNIyHuc2Vj/kBmk8jrK2lN+eLVq1bzvqXFcq1atcn2ZJYcps2EUCQWj\nzNrTG5mbnW3ZXiMcdL9VjEAb9NUEvmHDhl6xebXi0fNVsUaVGy4WVP7qnnvuAWCvvfYCYObMmTm7\nBlNmwygScr6fWXaVVFXhDLV3WblypVeG1196NlaDMnBqrlk/cm9vMvVe3z2hv/76K+BKF/sJwput\nkj5qCh+vBK2ItJlzQa6eodR31KhRXqugjh07AnDxxRcDMHLkSCDYRnEFF5rScmubbbYBnGNEFSj1\nMq9atYpjjz0WcLWmn3zyScC9zKpWqaqd6sV0ySWXALBo0SKg8uVWnyp1JfR/yArpZVbZGj0TjVP3\nLtamFNWj1kTmJ5uXecyYMQBcf/31gOs+2aJFi6jf819Xs2bNvKqsMpHUpzkM8vEM4703Gq96a/Xu\n3TuIc1loyjBKiZwpsxRYyqhld5cuXQA47bTTgMpqjgsWLACcmkrN9X91DlStZVV8HDp0KOBUavHi\nxXzzzTcJr6uQlFndIP1dIoPsIJjJGPv37w84db3vvvsA6NmzJwDffvst4Ppq16pVy3sGQTgn1b/6\n8MMPj/nzXD/DRGNq3rw5gPcZtrrZhmGkTeChqVghJnCF/Nq2bQu4Qn5SXdkaFRUVXi+m0aNHA67Y\nn5w8rVu3BlwoZODAgQB8//33gCvbumbNmqQF7woJXauUOd+FG9SxUaGngw46CHBhF9n0KqOrlcXY\nsWO9ZzRv3rysryOeIueaVFYZN9xwAwA//PADALNmzQLwOnyEiSmzYRQJgdjMkQriP57fQ6sUQPXj\nveWWWwBnUx999NG88847AJ4nWoH34447DoBu3boBrnOgipP36dMHgJ9//hmoDCXccccdQPwkhUKw\nmf39l7QLScXw0zlGIm89pDZGrZKUtKPnq2ek69J9nzhxIuBs6IqKCu8554Kwn2Eq74jCqJ07dwaq\nJosE6feIhymzYRQJOd8CufvuuwPw+OOPR31fytmlSxfPK6rvKUm/Xbt2AIwfPx5wKiQb+eabbwac\ntxWcuki5VqxYEXXefCqz7MqFCxcCTuFkm/oVOxOSKfOll14KwLBhw7zv6Z7JMztixIio6xJqR6Pr\n1GepadOmGbebkd9ApOLrCOsZpvJu+McuFP/XytSU2TCMlAncmx0vfVJJ+V9++SXgPLZCvZjLyso8\nZahTpw7gGqadeeaZgLPpFF+W91uZX1KU+fPne170QuTNN98EYIsttoj6fjI1CnKDSaQiC614dH3K\n5mrWrBngVkDaTCFiNYGLt1lG34/cNglubBdccAGA5/PIJfvvv3/S30mmtFpdKgITRM5AMkyZDaNI\nyLnN3KRJE8DFKhWbVDvTe++9l/bt2wNOAV566SXAJa9LiaXcW2+9NeBsuHTIh80sb7UaxUWcP/Bz\nZZMB5vdqX3jhhQDcfvvtMX9fq6DVq1fTpk0bwHl1GzduDLjsPD1Df065cvYnTZoUdc5EBP0Mk70T\nqTwnjU/3Lp2/jXE9ZjMbRikRenEC2UL6KntKmUE77rgj4DJl5syZ49lRsjfU3LpGjRqAy/Tadddd\ngfjFCwqRdevWefFZKXOhFleQqiiuL/tV1zt8+PCo/8sPcu2113o2o77n91LH2+Ul+1zZZ2VlZTm7\nP4ceemjCn6ejqvF+N14+QBCYMhtGkZAzm1nxNnm15cHVzqd3333X+13ZG+KPP/4AYPny5YCzw844\n4wzAKXYmsc1C2HGj7wURV45x7Ixt5nhec///586dCzhV/fbbb73f2WGHHVI6l3ZmSf3PP/987+/P\nO++8hH8b1DNUPsNXX30V9X3t577uuutSPlYQdnfEsQqrOIGQo0vbGd977z0AjjjiCKByOaYXX8nq\nCsDL0aXtkvpbpW/6K5OkQq5eZjmAVK0jkjDDFWHUzX766acBl16r5bacVX379mXIkCGAS/1Uaq5C\nkNOmTQMqHZ7gkom0JVYT+owZM7znH3ZKrpa+/ueh8/tNhVjIvJBI+TEHmGEYScmZMvuT9ZUieMgh\nhwBOZWvWrOk5vrQJQxUP5ZB59tlnAbfsPuuss4CqS5tUnCf5XGbLcaeVSEjny1iZ/amwSvhREo8/\naUTPtG/fvtx2220AXHnllQBeqEqbY7R9VWE6fwqpQlQ33ngjgwYN0liSjjGbZxjv+LVq1QKqpgJH\nolXjd999l/Accu6msxHFlNkwSozQlNnvPNH/ZXcoLKPZTgkHa9eu9Watq666KuqrlPi1114D8Owy\nhbkyKUCQK2WWCkc6uXJRfCAIm1nPTM9S99n/2dGzPOussxg1ahTgnJNafcgWlor369cv6hj+Zzhv\n3jxvQ0q8+xW2MivBKdJJK/v6k08+AdwmoF9++QWomqKbaBWmY8VzgJoyG0aJkTNllt3h/7lSMCMT\nPzR76W8+//xzwHm3lWii2VAhKZWxSScgn4+N7VI6eUnDJBtlln9Dz0jJO/JvSEk0DiWI1K5dm5tu\nugmAwYMHR/1MaCWmZ61NHQcffHDU9//8808mTJgAwEknnZR0jGEos39FsHr16ipJL/7x+D3fWonK\n253mdZkyG0YpEbgb1V9qRuoqG0JxVtlXiVRU6XWaBbVJQ+mcQjNqIaVFavUQi1wochD4NwsceeSR\nQFXbTs8nUq0GDBgAwNVXXw3AW2+9BbiCDNpgI7SJRvFoJaJsuummKcV3w0SfK8W5Tz31VK/IvZBn\nP97nORNY+6fnAAAOpUlEQVRFThdTZsMoEgJR5sceewyAXr16ebO2MrqUCaN4ssq2vv3220DVbYt1\n69alV69egPNiqz2Lig+oGLuUQ7ZyISmzlOWaa64BnO2Y7/K56SA7UNes56z+YEq5TISUVpEIxaiF\nntn7778PQIMGDaoco1BWMoqy+FU5Ev+qJZfP25TZMIqEQLzZKhKwYsUKtt9+e8DZSioCJ4+0ZmCV\nq5EXW/ZwjRo1ePXVVwHnGfzxxx+jzte1a1fAZSRlo8i52tiu8ae68SAowsjNFnrGWnVkgvK7n3nm\nmYyPEdQz1MqvUaNGGV+L4uTKQddWTm0wygTzZhtGiRFoEfyNNtqIBx54AHBebH/c8KGHHgLcDKYC\nAzpG27Ztvb+VIiubSI3h5BGVXZoNYSmzMoG0alEmVK4JU5ljnKvKv2VDavyyf7WLTLkDWZ431F1T\niVCbJbUTlv8mSEyZDaPECDQDrHbt2t6eYsWT5fkU2nssr6YKD0jBVq5c6cU15bU+/fTTAdhuu+0A\nmD59OhCM9zqoWV1eedn+iitKkeLtxQ2bXCpzJgRRNjjo1ZVKOGsHl/6vpofgbGBFXrQiDQNTZsMo\nMQLNAPvjjz88T+A555wDuNikYsWqNKKZWMr10UcfAZWZQVdccQUAH374IeBausoOLQRUKP3EE08E\n3Eyt8XXv3h3InyKnS5CF9QvxfOkgn4wfZbjdcsstXgw+TEVOl8A3WsjhoQ+3Qk/aPqYl8rHHHgu4\nzoFylM2YMcOrXjl//vyUry1TCqELZJgU2jI7jJe41J5hPGyZbRhFQs4L+hUapTarr49jVCrwlClT\nYv681J5hPEyZDaNIMGXOcFZXwTnVWi5UikGZk2HKXIkps2EUCabMJTarF/sYi318iTBlNowiIS1l\nNgyjcDFlNowiwV5mwygS0srNLnbngsYXZEPsWMfypzRmc75tttkGqGyjCq6i6csvv6xzmANsPadg\nW7oWGvn4IKioe7du3UI/l73M6z/mzTaMEsOUOcasrgbh6RQub9++PQCzZ88Ggl2qC7WLUQGIVJ6d\nKfP6jymzYZQYpswxZvVC3jgP7vo22WSTKk0E/ORLmbWRP9fN8fL1GVUJ5c8++yzwY5syG0aJYcqc\n5azeqVMnwLUkjWzVk09ks69Zsyb0Ivg333wz4BocLF261Ksko/JKEydOBFxRRhWcVwPBbNq45FqZ\nN910U89voetXWSx9TbZiSodUlTnwLpC5RJ0WP/3007xdg6qNijZt2gCuK6C/b+/ff//tvWhaiqpn\nVmSP6kg0MYwZMwZIzakWpONNaCn53XffAa6TxX777Qe46pXvvfdelV7ZEo1tt90WcL21dV8KAT0P\n9bvS/y+77DIA+vXrV+Vv9PKKpUuXAq7kVS47mNgy2zCKhPVymS01VM/nbMh2iXbjjTcCcOaZZwJu\nJl61ahXglluqWrpgwQIvWUShplmzZgGu77R+PnnyZAA6dOgAuG4JH3/8sa49rfFBemNUUUaNQSqq\n+y8F04pCPZgPOOAAr9qqOlaoK6j+5tJLLwVg0KBBQHaOsnSfod/B+cknnwCwxx57AO7ZSZnVfSUd\nguz+aA4wwygxCsdgiYG6PMrO8hN0YkY6IamNN94YgDvuuAOorKUMLlVTvYulOFJugBdffBFw1y+b\nWTW21Q1k8eLFAPTu3Rtw/arlXBo/fnw6w0sbKfKBBx4IwMKFC6Out2PHjgC88cYbAHTu3Nn72112\n2SXmMeUw1GojH72X9XxVl12JPnou6uCYDffffz/g6sfnIsxpymwYRUIgNrNm8EQ9aDfaaCPA2VDq\nNSWkUptttpnnERT+a/z1118BZ3/tvvvugJtp0yEVe0u9r2bMmEH//v0B56XeZ599ADj33HMB17lS\nPbSkngpZ6T7EQseQ2uu8ujdqDqCGAfXq1UvaozoTm3nzzTcH3H2O+FvArYSuvfZawPkNEn2Wrrvu\nuqi/ERpbLntN6Zy33XYb4FY+Rx11FADTpk3L+FriEVToLRGmzIZRJOTcm639tvLUKqlg7733Bipn\nS9lkurY999wTcC1unnrqKcD1ecqGRLO67GLZsmvXrvU8nPJ4apaXEpeXlwNOVfU10cwspZPNJq+q\nFNIfi9V9mT17ttffOpXxxRpjIvw+CY1BY1TvL3nlY/HCCy8AcNBBBwHunsoDrvuZDdlGJDQ+jVcR\nCeUv6H63aNECqLzvGof/OQuNb6eddoo6x7x589K9PFNmwyg1cqbM8lpKZRR3nDRpUtK/1TXqq+Ks\n2naYDenM6mvXrvX6SEuJ/bO6ZmStLqRisZDdPWPGDACWL18OuA6Sydh8881ZtmxZ1HX4PfKFsgXS\nf336PCTyIaRKWOmc6rUtP0gk8tMohTXZe6SKMMqeSwdTZsMoMXKmzP7zSMES5ebKmyr7Wl5Hodnx\ngw8+yPSyEs7qseLO/lWC3xZWtpBsI20wkKe6bt26nrdeY2/WrBngcs3feeedqGPp9/xe7bPPPpuZ\nM2fGvVb/+GKNMVcsWLAAcAr1zTffAMG098nnFsi6desCyQtZmDfbMIyUCV2Z4x0/lfhiDJWJ+tsg\nSDSrSxG1ilixYoXntfTbwrIJ9VX2rz9/vLy8nBo1agCu/I/sRx1TedzPPfcc4LzFTZs2BaBv374A\n9O/f3/N8BxlnDoOXXnoJcNGMsHKX8zW+ePe/fv36AJ5vI8NjmzIbRimRN2WOOGbU/08++WTGjh2b\n6vWkezlVSMVmjsxOU3aQ9i37begBAwYAMGzYMMAptRR9zZo1Uf+OROfZcsstAbwY8tlnnw24nGHt\nSGrVqpWXtaSdP1L7WOOLNcawadmyJeBa4ArZ+sohyIZ8KLOeoaIW8Qj6M5rwXPl+mbUM8adwpoPf\n+ZPODYz1QfC/bDreb7/9Rq1atYCqmyR0bhUlSPaQE6GQiBITtNFhxIgRgEvWWL16tbf01jUq1CPn\nWZgvcyobU+L9TNcZxEaLXL/M5eXlXtMBmUR+4j2PTLBltmGUGKFvgdSMFC85YMmSJVW+p036SgqJ\n5zzQhgMhlc+2MqRfkaUu9erVq6LEkeWAYv0/HVQfq0ePHgDcfffdANx1112Aq5slNVi7dm2VZWo2\nCpAuiRQ52fJZ5sgNN9wQ6DWFiZ6tUnlTwf88evbsCbgSUEFiymwYRULgNrPfRlB3CCUNSDVlW/rP\nHxl28m+5E/5UQFWJHDJkSMpjEenYW3Xq1OG0004D4PbbbwdcssDcuXMBt6EgXnG+RGgL6b777gu4\nJBmlryqFVOeuqKjgjDPOAODJJ58Eqtr7+XCArVy50rP3/ej57rzzzoAreCCfSSw7XKG8eIqYK5tZ\nz0cVOWOh+x+vYEaiRKR4vh6zmQ2jxAjdmy1FVkJE48aN/cdMegz/NUrtVeAuG9KZ1Tt16uQVA5Bd\nL/R/eZc1i8eynTVmJYMowUTIaz1y5EgApkyZArjVTKwUWH8iTcSqJnRl1vN58MEHAZfUEonGKEV+\n/PHHAVemN8vzZ6TM2jRz5513Am4lpHt30UUXAa6IQZJrANxWXm3X9aOVnPw7qZS8MmU2jBKjoEvt\n+q8tyG1zEedIeVavXr26l6Tx8MMPA04t5SOQPaUEfNl5KmQ3e/Zs7280Kx9//PGA25QxatSoqJ8P\nHToUqCwuH8mUKVPo2rUrEN97HqbNLLVNVJxAhR1U9E/JNiqYH0Tnh0yVWc8m0TbVTNlqq60AVyZL\n6DOt3IGpU6cmPZYps2GUGAVdatdPECVm0sHveayoqPDK4MjmUzaWCtX16dMHgNNPPx2AL774AnC+\ngkWLFnleaXlpVaZGRQnq1asHQOvWrQFXYM6/MikrK/OuLV6KaBjIPld7mltvvTXu7/p9JbIpmzdv\nDrgogH4vInMt6MuuwimnnALA008/Hfix5aVX+WH5PTQuFaYIElNmwygSClKZ46lLOpk3QRArmV7X\npmZiUm95mFXu9+KLLwacmsrebdSokVdqRvFjqbpsZam/ih1KrZQ1pXM2bNjQWxnkQpGFViUnn3wy\n4MYoG7+8vNyzlXfbbTfAbX1UdEOrjnileZT9pwL1YRBGEwH/ikKrKDWY00pNG02qVasW2CrElNkw\nioSCVOZ4xQdOOumknF5HLA+xFPCvv/4CnHr7Y79qTyL1UobWm2++yU033QS4UkJvv/024HKvL7/8\n8qhzadwqVqCZfMmSJVVm9TBtZ60IVPj/9ddfB5ynXr6A5s2be/aoytXKLpUNqS2RasEj76+uX1s6\nwyTTPPbZs2d7DRjk31CEQisS7TlQyatjjjkGcN77IIszCFNmwygSCjLOLE+gsqmE7FHtJpKNmQ2Z\nxij9RdCFZnt5euXV1n2uXr26Z2NqVo84f9QxpF6yO6W2yoCTvZyIXORmS5Xkld9tt90YN24c4Eop\na0xqGHf99dcDzhN++OGHA66YoVQ+FYLOzZZ9q0IPauSnxn2RxTP83ne1u/VnOmay1z7iby3ObBil\nREEqs3KulTsrZIeobUsQpDKrJ2od629PItXV34wePRpwWV6RSq57P3DgQACOO+44ANq1awdAly5d\nAGd/ywOsY/pLDycbX6IxhkW/fv0At9NLZYS0KgnCW53Pgn4qFewvixQkBVM2KAiUiCGniEI7QZDO\nByEyjOC/b1tvvTXglmRaZmlCkomwYsUKL/lFDjaVoFEihWqAKbHAP5mk0pc6lxstYqExKvSkjSi6\nLk1qQRRTKITqnGFiy2zDKDEKUpnVOU9JFdk4D5KRzqwemT4ZDymRwkyJlubpho/k+IrsnqCNC/G6\nC+Z7mZ0LTJkrMWU2jCIh78osm9K/QT9XhDWrqziBf4tfInXv1q0bABMmTABccsb06dOBzIoF5kKZ\n/f2zc40pcyWmzIZRJORdmfNNrmf1srKyKgXStTpRyE0dEpUymg5+T7fZzOs/psyGUWKkpcyGYRQu\npsyGUSTYy2wYRYK9zIZRJNjLbBhFgr3MhlEk2MtsGEWCvcyGUSTYy2wYRYK9zIZRJNjLbBhFwv8B\nIuPJbRnKuPwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197621650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 3750, D: 0.2431, G:0.1514\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmA2jRPh/xtBbvUZl5PgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197150fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n"
     ]
    }
   ],
   "source": [
    "D_LS = discriminator().type(dtype)\n",
    "G_LS = generator().type(dtype)\n",
    "\n",
    "D_LS_solver = get_optimizer(D_LS)\n",
    "G_LS_solver = get_optimizer(G_LS)\n",
    "\n",
    "run_a_gan(D_LS, G_LS, D_LS_solver, G_LS_solver, ls_discriminator_loss, ls_generator_loss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# INLINE QUESTION 1\n",
    "Describe how the visual quality of the samples changes over the course of training. Do you notice anything about the distribution of the samples? How do the results change across different training runs?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As in the TensorFlow notebook, the network outputs similar images for different noise inputs in the beginning. After further training, the number of classes it starts to generate diversifies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Deeply Convolutional GANs\n",
    "In the first part of the notebook, we implemented an almost direct copy of the original GAN network from Ian Goodfellow. However, this network architecture allows no real spatial reasoning. It is unable to reason about things like \"sharp edges\" in general because it lacks any convolutional layers. Thus, in this section, we will implement some of the ideas from [DCGAN](https://arxiv.org/abs/1511.06434), where we use convolutional networks \n",
    "\n",
    "#### Discriminator\n",
    "We will use a discriminator inspired by the TensorFlow MNIST classification tutorial, which is able to get above 99% accuracy on the MNIST dataset fairly quickly. \n",
    "* Reshape into image tensor (Use Unflatten!)\n",
    "* 32 Filters, 5x5, Stride 1, Leaky ReLU(alpha=0.01)\n",
    "* Max Pool 2x2, Stride 2\n",
    "* 64 Filters, 5x5, Stride 1, Leaky ReLU(alpha=0.01)\n",
    "* Max Pool 2x2, Stride 2\n",
    "* Flatten\n",
    "* Fully Connected size 4 x 4 x 64, Leaky ReLU(alpha=0.01)\n",
    "* Fully Connected size 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([128, 1])\n"
     ]
    }
   ],
   "source": [
    "def build_dc_classifier():\n",
    "    \"\"\"\n",
    "    Build and return a PyTorch model for the DCGAN discriminator implementing\n",
    "    the architecture above.\n",
    "    \"\"\"\n",
    "    return nn.Sequential(\n",
    "        ###########################\n",
    "        ######### TO DO ###########\n",
    "        ###########################\n",
    "        Unflatten(batch_size, 1, 28, 28),\n",
    "        nn.Conv2d(1, 32, kernel_size=5, stride=1),\n",
    "        nn.LeakyReLU(negative_slope=0.01, inplace=True),\n",
    "        nn.MaxPool2d(2, stride=2),\n",
    "        nn.Conv2d(32, 64, kernel_size=5, stride=1),\n",
    "        nn.LeakyReLU(negative_slope=0.01, inplace=True),\n",
    "        nn.MaxPool2d(2, stride=2),\n",
    "        Flatten(),\n",
    "        nn.Linear(1024, 1024),\n",
    "        nn.LeakyReLU(negative_slope=0.01, inplace=True),\n",
    "        nn.Linear(1024, 1))\n",
    "\n",
    "data = Variable(loader_train.__iter__().next()[0]).type(dtype)\n",
    "b = build_dc_classifier().type(dtype)\n",
    "out = b(data)\n",
    "print(out.size())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the number of parameters in your classifier as a sanity check:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct number of parameters in generator.\n"
     ]
    }
   ],
   "source": [
    "def test_dc_classifer(true_count=1102721):\n",
    "    model = build_dc_classifier()\n",
    "    cur_count = count_params(model)\n",
    "    if cur_count != true_count:\n",
    "        print('Incorrect number of parameters in generator. Check your achitecture.')\n",
    "    else:\n",
    "        print('Correct number of parameters in generator.')\n",
    "\n",
    "test_dc_classifer()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Generator\n",
    "For the generator, we will copy the architecture exactly from the [InfoGAN paper](https://arxiv.org/pdf/1606.03657.pdf). See Appendix C.1 MNIST. See the documentation for [tf.nn.conv2d_transpose](https://www.tensorflow.org/api_docs/python/tf/nn/conv2d_transpose). We are always \"training\" in GAN mode. \n",
    "* Fully connected of size 1024, ReLU\n",
    "* BatchNorm\n",
    "* Fully connected of size 7 x 7 x 128, ReLU\n",
    "* BatchNorm\n",
    "* Reshape into Image Tensor\n",
    "* 64 conv2d^T filters of 4x4, stride 2, 'same' padding, ReLU\n",
    "* BatchNorm\n",
    "* 1 conv2d^T filter of 4x4, stride 2, 'same' padding, TanH\n",
    "* Should have a 28x28x1 image, reshape back into 784 vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([128, 784])"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def build_dc_generator(noise_dim=NOISE_DIM):\n",
    "    \"\"\"\n",
    "    Build and return a PyTorch model implementing the DCGAN generator using\n",
    "    the architecture described above.\n",
    "    \"\"\"\n",
    "    return nn.Sequential(\n",
    "        ###########################\n",
    "        ######### TO DO ###########\n",
    "        ###########################\n",
    "        nn.Linear(noise_dim, 1024),\n",
    "        nn.ReLU(inplace=True),\n",
    "        nn.BatchNorm1d(1024),\n",
    "        nn.Linear(1024, 7*7*128),\n",
    "        nn.ReLU(inplace=True),\n",
    "        nn.BatchNorm1d(7*7*128),\n",
    "        Unflatten(batch_size, 128, 7, 7),\n",
    "        nn.ConvTranspose2d(128, 64, kernel_size=4, stride=2, padding=1),\n",
    "        nn.ReLU(inplace=True),\n",
    "        nn.BatchNorm2d(64),\n",
    "        nn.ConvTranspose2d(64, 1, kernel_size=4, stride=2, padding=1),\n",
    "        nn.Tanh(),\n",
    "        Flatten())\n",
    "\n",
    "test_g_gan = build_dc_generator().type(dtype)\n",
    "test_g_gan.apply(initialize_weights)\n",
    "\n",
    "fake_seed = Variable(torch.randn(batch_size, NOISE_DIM)).type(dtype)\n",
    "fake_images = test_g_gan.forward(fake_seed)\n",
    "fake_images.size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the number of parameters in your generator as a sanity check:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct number of parameters in generator.\n"
     ]
    }
   ],
   "source": [
    "def test_dc_generator(true_count=6580801):\n",
    "    model = build_dc_generator(4)\n",
    "    cur_count = count_params(model)\n",
    "    if cur_count != true_count:\n",
    "        print('Incorrect number of parameters in generator. Check your achitecture.')\n",
    "    else:\n",
    "        print('Correct number of parameters in generator.')\n",
    "\n",
    "test_dc_generator()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter: 0, D: 1.349, G:0.2757\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3We0VtXVB/ppREBEpdg1saKCKMGGFY2xoS/6RokKigbF\nhsYaMRqxR+wtiCh2kWIhhhBbFGOKNSjWIKjYo6KABbDm3A+M39zP2WBynow7xn3vcc8vcM55yt5r\nrz3/Zc619mINDQ1RRRVV/P8/vvf/9QFUUUUV/+9EdTNXUUUziepmrqKKZhLVzVxFFc0kqpu5iiqa\nSVQ3cxVVNJOobuYqqmgmUd3MVVTRTKK6mauooplEi3pefP755zdERKy22moREfHhhx9GRMQ///nP\niIjo0KFD3H777RERccABB0Ttaz///POIiFhzzTUjImLKlCkREfH9738/IiJatmwZERFLLLFE3Hzz\nzRER0b9//4iIeOyxxyIiYumll46IiG+++SYiIrbddtuIiPje9xbkpNNOOy0iItq1axcREVtssUV8\n8cUXjY7x66+/joiIVVZZxXsWc379+/dviIiYP39+REQss8wyERGxwQYbRETEK6+8EhtvvHFERMyc\nOTMiIl5++eWIiOjWrVujz/3Xv/4VEREPPvhgRER07949IiLmzp0bbdq0iYiIpZZaKiIi1l577YiI\n+N3vfhcRERtttFFERMyYMSMiIj777LOIiFhrrbUiIuLvf/97RERsvvnmMWvWrEav+fjjjxt99sUX\nX5znFxFx9tlnN0REzJkzJyIiVlxxxYiIaN26dUREPPvsszF37txG5+Q4jPf7778fERFPP/10RESs\nvPLKEVFcn/feey+/3zi0b98+IiI++uijiIho27ZtRESsu+66jc5ppZVWioiIZZddNiIWXC/X7Jln\nnomIiBVWWCEiirEePHhwnuMvfvGLhoiId999NyIix9o8aNWqVWyxxRYREfHpp59GRDEXDzzwwIiI\neOmllyKimJMffPBBREQst9xyERGx/PLL5zW7/PLLIyKiT58+ERHx6KOPNvq+zp07R0TEX/7yl4go\n7of11lsvv9trfd8nn3wSEREtWiy4Pa+99tpG1/Dboq6b2YdPnz49IiJefPHFRic5ffr0uOyyyyIi\n4h//+EdEFDdax44dIyLij3/8Y0QUA+T3G264YUREDBo0KH74wx9GRMRZZ50VERHrrLNOREScc845\nERGx5557OsmIiDj++OMjImLXXXdt9FkzZsyIffbZJyIijjrqqIgoJpfBrI0BAwZERMSf//zniIjo\n1atXRETcdtttERExe/bsmDdvXqP377DDDhERMX78+IiIuPXWWyMi4qc//WlERPTr1y8iIsaOHRsR\nEe+8805OtJEjR0ZEcWNJDP/7v/8bEcUE2GmnnSIi4uijj46IiJtuuikiIp588sk8DgnMeE+dOnWh\n84soJrcbokuXLhER8fDDD0fEgmt46aWXRsSCGzuiuGnuuuuuiCiSysCBAyOimIS1iUtS8d7rrrsu\nIoqJ+stf/jIiiuviRgUQxuKuu+6Kn/zkJxFR3DAPPPBAREQ88cQTC51fp06dIqK4QZ3nQQcdFBER\nN998c95wHTp0iIhiPjmmww8/PCKKeXX22WdHRMQ999wTEQtuZp+x1157RUTEb3/72xy/iCIZ3X//\n/RERce6550ZExBFHHBERRRL49NNP43/+538iokisrrsE3dSoaHYVVTSTqAuZy4EyQOxvvvkmke+O\nO+5o9BpZ/r777ouIiDfffDMiIoYOHRoRRUYbM2ZM0jvU9L333ouIiL333jsiiuzbtWvXRp8B0Swe\n6dKlS1J09H733XePiIi//e1vC53P22+/HREF1UN/tttuu4hYgGqyNUR2nttss01EFHQSijl/qDJw\n4MDM0r4PbYV00AQCooNo4I033hgREaecckoiwPnnnx8RkSj2bcj8+uuv59hEFFTZ+Jx88slx1VVX\nRUSBqig4FgCVVl111YgoaOkee+wRERGXXHJJMiLoSbIsttgCxojJ/OpXv4qIiD/96U8REfHQQw9F\nRIHgn332WTzyyCMRUVwPtP+rr75a6PyWWGKJiCiQGHscPXp0RCxAv9mzZ0dEMW+nTZsWERHnnXde\nRBTzbf3114+IQtbtvPPOEbGAxZh75rs5IshK880xm7uu4TrrrBOXXHJJ/j8iYpNNNomIiOeee26h\n8/t3USFzFVU0k6gLmSEF04VOGz58eERETJo0KXr06BERRaa98MILIyLi5z//eUREXH311RFR6FKa\nA/o89thjseOOO0ZEobvpzp/97GcREbHvvvtGRJHt6FPHceWVV0bEArOD0cKwYFztsssuC52f85o0\naVJEFOYMjbr88sunOSeLM8QgwsEHHxwRBbrefffdjX4+44wzMitDHxkfItJoTCG6EmMZMmRIRCxg\nMRjAvffeGxGFCbj66qsvdH613wltITRUuOWWWxJFoQ6Da8kll4yIgjH5bmMg/vKXvyQCnXHGGRFR\nmIi+f6uttoqIiGuuuSYiCjZ0zDHHREShi99+++147bXXIiJiyy23zN9FFAhWG2PGjImIgrUx3Gjw\n66+/Pr2RNdZYIyIievbsGRGFAYkBOAfz7ve//31ELPBSeAzMNN/js10jHoY5jaEecsghEbFgjM0N\nLNK9gvE0NSpkrqKKZhJ1IbNM8fjjj0dEUeaRnXr37h0nnXRS/j8i4rDDDouIwi2lZ7feeuuIKFD1\nlltuiYiITTfdNJFAFqe7uH6cwOeffz4iIiZPnhwRRWZT2hkyZEg6xU899VREFKjtM2X72u/jztOX\nEKBv376pkSE7D8B50P6QhnMt+3/xxReptyE/RkE7cXaxHAyFdqOTZ8+eHaeffnpERPzmN79p9LfN\nNtssFhU/+MEPIqLQg46Pfpw3b17qXdrx17/+dUREXHDBBRFROPabb755o8+mU88555y8/pxZKL/4\n4otHRFFC22+//SKiYAgnnHBCRBQewGWXXZYO8JNPPhkRhf5WQqwN1RFzyHuUSqdOnZran36fMGFC\nRBQa1RzGCIwlT2bLLbfMz4C0mJnzOvnkkyOiYJ7mA5+BU73KKqtEq1atIqLwkZRksZmmRl03MyrM\nsHFArP1OnTolrR03blxEFCUZJ2lw3QTDhg2LiKKctMIKK8SIESMiorhYbkSlKTeUMpcbibHhZjzx\nxBOzzOAG+fGPf9zoPbWhbINmm2DKUTvttFNeHJMTnXNxXTQlFsaY827dunVSL+eh5KS05gZQG5d4\n0Fy0fMaMGVnblWidl4lJogiUePDgwRFR0EHfsfjii8edd94ZEUXiNYnJDZTVcRint956KyIWyBGS\n5dhjj42IwhwzUV1v1BbVdM2de//+/fPaKd2QWZJgbTAglYrQXjfmhAkT4he/+EVEFBSfWSV5mtfm\n7plnnhkRRclq/vz5semmm0ZEUQLzs3nPPPR7Cdz5mrs/+clP0pyTREgM5dumRkWzq6iimURdyIx2\nKZHIlBMnToyIBagAKTRcKJoznmQ5DSEsfXT46KOPzjIOgw3NUUKQQVEbCMJ0Y9BsuummyQgYRCgV\nqVAbPufEE0+MiAIlUNmnn346TROZ9w9/+ENEFFTYeaKTEAEyr7LKKtlkAbUxAaW3U045JSIivvzy\ny4goKCM2w7zq1KlT0kqoIeOjouVgGiphaYiBvn/9619TQjB8yBfoCW2hOeREFydMmJDHiCEwQhli\nuszQe6agcXvllVciYgGi6SbTlKJUZa7VhgYb1xvCK0XuvvvuKYWwK8eI3WAVGCipiOW8/fbbSYkZ\nh8I9wqRzfuaBa4nBPvLII0nJsdQf/ehHEVGMZ1OjQuYqqmgmURcyE+RMCzpAtrnxxhuzFCMTQp1B\ngwZFRIHEDDDaUk939+7d469//WtEFGimv5Vmp0uhkcaDchlo+vTpceSRR0ZEkYUhFqOoNiCAkhDD\nSZY/6aSTUhdef/31EVFkb2UM+l52Pe644yKi0EH33HNPMgxtq/Qj406b5wsvvBARRf/6FVdcEREF\nckyZMiXHQLuk8dRHXQ5+guOiZaHSyiuvnDqQlsSQ6D8ooyGGcUgPbrvttsmalK+8F6tTfqO7MTmG\nkmv86aef5muV3YwP9KsNhp755DVYxH333ZdGnuvtmHgu5hEfZPnll4+Igs3cddddifhMQPraNdRY\n495wXu4D86Fz587JYhwHpqsk1tSokLmKKppJLFbPvtmXXHJJQ0SBurKTZoannnoq3VRNIXQGpIAu\n77zzTkQUDq5C/WeffZaIqLEA6kFI5RX6VBaHOrTeZpttlg4sbbnbbrtFRJE5zzrrrFyRcsUVVzRE\nFK6x0hT9xu2OKEpvUJZe93vaD+LRx7feemvqeCjv/Ogvmdr30myvvvpqRBS6bOrUqekv+B2k4JCO\nGDGi0Yqbyy+/vCGiYDnG3bFsttlmOa7KORp96GrHw5sQ0HjjjTfOsqV2SiUZehcSc/aV7iAp5Fp+\n+eWzfGiMzTElsuHDh+c5nnHGGQ0RhSbH0jjDf/vb37Kxx3U2b1xL52FsoDrn//777892WePGE1Ai\n5POoftDI2JZxeOSRR5IB8F3KzVm33HJLk1ZNVchcRRXNJOrSzDQF3UtLqP9ecMEFidb0BQ0BgaG4\nLAux6bLx48fnggPLKWlKGk7DA+SkPSEnx/Tcc89tVPuMKDKndrragCacVTVLdc1a55Emk01pcech\nq3Lpa9cwYwkQkCfAk6AvZXGOs3Gm0z/44INEEcgDbTjh5VBDdZ2wAUi2ww47xEUXXRQRha5VtbDI\nhGdSXrMLwffYY49cwOFcacbyvMDyzAd/1446ffr0bNH0HpWIRTWNGGdz9IYbboiIAs2//PLLdN9p\nf0zp1FNPjYhCk2MLfAmLJrp165bLJXkyeiPUmV1bDOnQQw+NiKJpyb+TJ09O1qJKg4E5zqZGhcxV\nVNFMoi7NPGzYsIaIIhNDjjfeeCMiFmR9DjTnUfcU1KElaSNoCOE++eSTRGDHJgPTPzQxBOOIamZX\nRzzuuOPSCdai6D26f4YOHbqQZrZoHTLT12uttVa6lprhZWjuuI4wY8QbUG8/44wz8jy0sNLI/pWp\noSvvgP7XxTZt2rRcBmgM6D7fe/bZZzfSW4cddlhDRIGuGIRa63PPPZdMxCYFNJxlklBGBxsHWTvn\nueeem8iq0wzqQR3I6VqqbmBVaq4//elPkw1xn/kPzvGiiy7KczzhhBMaIop5pyZumexqq62WPoa6\nPqZjvI0N1uDaaf9ce+21c0xcK/0GWk8xDVUN580j0A/wox/9KOcBP8fxqBKcc845lWauoorvUtSl\nmaGAzC270FuXXHJJZpfy9kCcUB1YtCV9Jju9+eabqSdka91ishzEpqm5jZY5el337t2zU0v91dJF\n6FgbWANkp/csiJg9e3Zmet8NSSyN5ExCanVnyxtnz56dupbehbxq8lhLjVsbEYXe5YxOnTo134sx\n6JPnb5RDB5uFDHQhJO3Tp09qdA4t1FZN4HJjN/7u57vvvju72IwPVxtCYiHGWn83ZONpPPDAA8mm\nnDc0XFSd2Zja5EDlw3uXXHLJPC961iIgHgFfpW/fvhFR1IrV8keOHJnXWa+7cXXc2GW5r1zPOI/l\noIMOyvHEdI1NvQstKmSuoopmEnUhs3puecO97bffPiIWuK00kKynnkgz+QxamU6RDVddddWsMUJv\nWd5ny3KQTMcWlxMarLPOOpmpOa2yLM2zqFDfxRB0uj3zzDPZ+6uDSn+wjGy5ICSms5zn9ddfn+NH\nx9Nb6p82jrPCiFbEcnx2586dU1dhRGqmOt7KwV3HOnSyOddLLrkkz0kt1WdDIdpZD7elqTRoixYt\nEv0saVRLNy8cNy3peOhuTG2ttdZKRqLjjPtsHGujVtdGFF18XO5Zs2ZljzfG5Tz5HzqvICXmYb7P\nnz8/qzOuCfaEkTlPjr9rzKOwmcH999+f7IFWhsx6AZoaFTJXUUUzif9KM6vZ0Zj0wVNPPZXIa9M6\nGwnQaF6rj9frIfj777+f77Eyhe7keNM/1qWqVZdX0dx44435N8gJkaFfbcjidJy6H1R9/PHHUwPR\npPSvDiy1bw4/bQVle/bsmchmixyaEGrS92queqXV19XO99xzz2Q4VjYZK9emHBCKU49V8T3eeuut\n1HBew1mGIDaD4EjzH9RYBw8enKyKd4LduN6uLd0LHdWnMbm2bdvmqjWoq8vN5hS1oZ+AF+D89Ftv\nuOGGyVrUvnVrWaVU3vLYfFDB6Nq1a3Y2QmhsyTVSWcEy9UoI1+m6665LhgmR1bPVrpsadd3MSgEm\nRNkw+vLLL3MwlXfQUZa8ieBGMYCs/M8//zxLLxriy4sD3DgGEl0yEQzKqFGj0sxBg5Q13Gy1gb4r\nZ0kOtXsuuwiOgaGDzpvgbnrSAEX785//nGNgoit9SQSaI1A0hg8ZoQz15Zdf5oRE0cr7V5WjvJuk\nnyWlk046KScgGaA0w6TSRIF+Oi5j07t370yADLnyvnGSh/GTlBikGjcOPvjgNMXMLd+3KJPP+aO/\njDeS4JprrsmyoTkowdsUAmiZd5KrpLLGGmtkgmPguhdsMKA5yr3ClDVGtXtxu1YaUMit8vLK/xQV\nza6iimYSdSEzKofmsu7Rw/fffz8pguyp8I7CMjE0mkMEn3HllVcmAvsXcu2///4RUWRIJgokkVEZ\nMqeffnouK5OFUXglptqANP42atSoiCiWpG288cZJ16EoJCkbPb7XwhLn/8EHH+Rumwwjr8FOIIVm\nGWYQes7A2W+//ZIKuzYoMoOlHBDTd2EUJMv06dOTZmImaK1/XVPf6TxQ6Ntuuy3NpIsvvjgiCkYE\n5ZiMvt+iDVIKLX3iiSfS8CLFXBfjWBsaWCCzEhBpst5662XZyncx4VwHzAmtd8yoeocOHdLo8rfy\nbpyQmRHH4PU67GD06NE5N+wlrnxqfjc1KmSuoopmEnW1c95zzz0NEUXGsgUQQ+zBBx/MzemUU+gQ\nSKAQblkb00T23XvvvRN5IDH0ZgRZ5KDNz7+0LVOlZcuWqZVoSlkQMxg/fny2yl166aUNEYU5Z8EH\nfdy2bdtkCRAYAkBvSC2rQgEot//+++fY0E8yMnYCcaAbDUUzWl767rvvpp6GCHwD7GTQoEGNWgG1\nrDJdIJfv/ulPf5q6lmZW+oP2jBm/d/zGZtiwYYlAvseiBjudMs0wNZ9FwysLbbrpprldkhKVeaF0\nc8EFF+Q5XnfddQ0RxWIZ10ebbc+ePXMc/c314Akohfq9ciPz9rrrrsuymKYdHon7CctjGmIm5kXt\nskdjYz4o02EvEydOrNo5q6jiuxR1IbMmdm2GXGda7pRTTkmXVMans2R+zfkcUntu05ivvfZa6lKZ\n0zI2OlzjhkYQTiLtLCsfcMABqe8cq2xOO9YutLjmmmsaIooFBspXylvvvvtuIrD2SUhC+1laaLmg\nbEv/zp49OzWaBQuQHwPhctsEgA7ULkmv9ejRI91iLqqfoeTo0aMbZfXBgwc3RBSlIte/9omUzoV2\nVy2AaBYqaJWFNv4+a9asZGK8CqineQKylbeEwqB89qxZs9Kj4SDzJzCUyy+/PM/xyCOPbKg9ZrrY\n/OvVq1eyBuVCSK9NmQNNt2MkGOinn36ax6cCwj9yXpqT+DjmknmHsfXu3Tv1tHnrsxz7GWecUSFz\nFVV8l6IuN1sWp4PVCOmFCRMmZDaTrWk62gIqWc7H/YZ+hx56aNZ5IRGEsAUL59PzmSEZpKtdIEFP\nc8CxCFqmNqCnGjndqVa9zTbb5OIPtWzIXH6YvKYZDimE3mKLLbLGTfurwdLV6uuWD0KG8rFPmTIl\nrwWkgLDOoRy+S8sr9LdZ/Pjx43PM+BnlRfzYlGvpetG/Rx99dM4Dx4xdaLawOMYYOH4IrnfhhRde\nSGSms/27qGsIEc03808zx1dffZXno/egvDG/2rFj0IBibF999dX8XAtU1MmxLN4AZsJNN1Z8h2HD\nhiUrVb0xzs67qVEhcxVVNJOoC5lpOtpVGxzX7ZNPPlloYT1trF2PzqGpLKuT1WfMmJEoJyNaXkar\nyW50MN3CAdUhNWTIkKwN6qaxeB8K6yKLKJx2mRJ61T4WxeYLkMy2wLSfgEi8A0h95JFHJsPhJ3gN\npFFPlZltpA4ROaErr7xyIr7FAXSl8SyHSoTWRC648enVq1duB+t7MQTIZAygvzozpO7bt2+6ud7j\nwQI8Bb6H+YHJWUpqbF555ZV09XVRmTMYEw0dUVQrLFes/ZyIBbVxzEcnGw/CvFLN0F2n0wxST58+\nPRem2FDRZ6jXQ2Y1cWPjdZ4rNmDAgGQCGIPrawtpY/efokLmKqpoJlEXMsu2NFz52cSzZs3KxQOW\nzcmCsrmaZFlDyVjjxo3LDAk1oLi6r2xnaxiOIS0lw/3mN7/JDhw1QzocQtQG5uFfziTtOG3atKzj\nQl7nR3fRZpx1x87lf/LJJ9Np5hPoJ6a/dHF5L6Smv6DP888/n2MiOLK+oxyOw3not6e9DzrooOwN\nN56uGcfcxvmQDcpjUEcccUR2RmFoXGwsxOIS1QbXBSrqHDv55JPTY4DE9CcGVhsQ0LFbiulazpgx\nI1kLt1ifuDq2Kgo0L8cPf/jD/BtmRqM7H8doTFRIMDr9D7Nnz86eB5/pPvu2J3l+W1TIXEUVzSTq\nQmYZm3ss++glveyyy3I1SHnxOSTgBqsDepCZLqdrr702e3xlVS6jfmhZXV+yz1af4zQ/++yzqb/1\nN9OBi3o8DSYgyg8hO/7441OT+jzuKQRyvlDMseuWGzRoUKKm7MxVhdBW63gvl9uSSBvtH3jggfk7\nmrz8WJRyYDPYFNRTF3/88cdzHCCXTjCdUZYGqu9b3lrbw6w3mUfhe6Gg6gKUVLdXZ9ZDv9xyy+VS\nx/LGCnyY2sBaMCbMQx17++23T5T2WmHVkkfalh8GoDKx3HLLJTt13dWReReYm3tEdyLWZ2517Ngx\nWaJ7R2+8821qVMhcRRXNJOrqALvyyisbIgqEpBNkuC5duuSG5eVOH64lR5A+gAL6gWfOnJmPPFW/\n5sByT2VbyA0t6SSOeZs2bdIBLn+vLp9jjjkmu2v22GOPhojCJXeekP6xxx7Lxe6O1yJ76OF8IRPt\nx/0cNWpUfr5aK5+BVjN2nHguO0S0Wqlbt275HrV4Y0ezDxs2rFH30MiRIxsiCtTFjHgYn3zySTIc\nzEDt1PE4bueq/m9jvHnz5mXvOvTmWUA77INOVQWhF/V026QgomAo5a1ozzvvvIW2SzZ3uPTGZfHF\nF89VUdiZ8/RanotrqJ8BUm655ZaJuOaBz+cnYEiqHNDeHNYt19DQkCivmmEc+T21j1D6d1EhcxVV\nNJP4rzrAZF1cXyfY2muvnQ4tfQ1FaTi6g14s70Ty4YcfZuYvPyaTVtLLypmVOf2dHll88cWzVkz3\ncRtpN6hY+z4a3A4XUH399dfPuqlVMI5NV5oN8nQ02WHEcXTu3Dnr547B8XN0oZGONrrTNq203bHH\nHpv96eUVZMa3HJx/f3cNffZWW22VaA11XBu9yZgCZqZ33vHfeOONiUDQjy+gMkBD0rIqGGWf4IUX\nXsjdaNS7+SDqwLWBnemhV8913dV/IwqdC2XVpKGp7jhegccD9erVK68hZqTX2vzmDWEitDKd7ziG\nDx+e5+qacMDr1cx13czoDaNDucmBzZgxI40VzeuaM2yfozThwqPl6Ogf/vCHLNKbVG4gN6+JgIpZ\nmFFL1SMWLOpgtGifY0wsas9lg4fWe4+2zrvuuisvioYOtNCSTk0D2ia9Hp1cZZVV0txxnMpLyhZ+\n1jQguWkm0BBxxx135JJTNxg6xyQsh+NV9pLAvL99+/ZZbik3mDBoTG5LE9FEpt+zzz6bjQ5MPc05\n5T3RjIsJLHxmnz590iQjp1ByTUIaNyIK8DCHSBaLKwYOHJjJkzQyn30uyqxF03kCnjlz5uSSTc+f\nNvfMTQlOAjLfyBtJrW/fvmmmuhecO7NWU85/iopmV1FFM4m6DLBrr722IaKgfZrilYgefvjhpEBa\n7/wru2iN1FwByZlCU6ZMSfpjEYZmfAgpk6JFzDUMgeny2GOPJZtQ+kKpGFeXXXZZmgs33XRTQ0SB\nJor5Mv+sWbOSYTDHGGLoIqSD6uWnUGyyySZpqCnxaQop7yVOzhg7TIUMmDJlSiK/bI72e23ZALME\n0mc4V9+90047pZxCCSE0VgPRSAnU2LkfffTRaY6RKF7LCGOaodBMSyUsxuXcuXPzM5hmKDuUHzVq\nVJ7j1Vdf3RBRLLU1vzTk7LHHHjl/lPj8bFMIlJk0LD87erHFFkuzzJwzH3yW4ycVNVhptMFEt956\n65QGNt/Qous7ap+l9e+iQuYqqmgmUZdmVqJgbvjZwou+fftmVqfJGCzKHVDTe2RkLYNXX311fob3\n0OYyP11IY9gShlHDlLjggguyWYMOpG0WteGd8ow2QZoWym222Wa52Z/yhvNTTqAnaVkZ2GYA77//\nfpYllJOYaVAcE3E+9CfdiV1sscUWiay0GKTDkMrBAFOaY/ZgASuvvHLqOa2hND50MT5KQ87DlkmH\nHnpoohtUZ076XlrW8ZefCcZ72HrrrdN/YGK6Bot6PrPFONgO/evYP/744yxb2Z7KHtdMOAYjFqFE\nxG9YZ511ciMBjMYcNK+MDYPVveLaaYz67LPP8rXmkGvhPU2NCpmrqKKZRF2a+ZJLLmmIKDIUd1kG\nefPNN1PHysh0hjZHrXGyLa2pzNCqVavMWrI3Z5yW0ApKD9NDXEfHsMEGG6Teoi2hrKxb++xbngBk\nNzZ03IYbbpjfCTU1odBOZWbiWb+QfObMmem4cmmhKdbg+ziyfnaeNNzdd9+dSGthC0ee03v++ec3\n0luXXXZZQ0RR+jFm0HWppZZK5uWzaMfa51RHFIjl+J3XxIkT09XVmgj9+C1YCH9ANcCWVK5xhw4d\n8nooc9HBUPzkk0/Oc/QMcZUO2yhpBJk9e3Z+J4bEz8AWXTPlOqjr+nzxxRd5DOaVeYB5Gjvv4a1g\niDa1WG0a6i9NAAAgAElEQVS11XKem7eus8UvI0eOrDRzFVV8l6IuZK6iiir+70aFzFVU0Uyiupmr\nqKKZRF2lKeYC88hqKQ0g77//fpo1Gi60FTI+NBMwuZSDGGGjR49Og0cZQ0mGqaNJhDHBIGHIKTFM\nnz49C/KOR4ucY+7Xr99Cq6a0NjqX2keHKnFoP2TKKa0w2PRq+37GyFNPPZVjYJ00g4mpphlHmYUR\n5pjt3rjaaqvluWovZIj599JLL21knpx11lkNEYV56Dw8LXHNNdfMZgxNLY7X+Gt6scrHmmg7oTz9\n9NP5GcZOQ4QyG9PM6i4NIT7bGEyYMCGvmd/paTdnzj777DzHn//85w0RhTFl7Bixu+66a5btlJHK\n462xiaHn9QzLadOmpYlmZZXrzujyvcbGOCshMo1nzpyZY+V4tDyb/1deeWWTDLC6bmYOnT5XC8Bd\n9K5du2b3lsUQ6qwutIvK7XVTq9f17t073WsXXMePyeOG8kxcLqvv9p39+vXL75U0JKBF9WZzEzng\nbgiOZENDQ9a61RndgLYyskzQgn1L4nzmlClTsgvIDa9e7lhNKo6nieIGVGddeuml8yY0wTmxFhqU\nw4S0JY1FMhbI/Otf/8rvMWHLm/BxqI2X/mQ33euvv56TVieUOrvjVO1QY+Uc215H4ujQoUNWPtT9\nJUbfVxu12x9FFElOF1+rVq1yPkmm5osurvJjeN2I6uh77LFHzmMOeLlLTu+A1zlPicF3DRo0KBeB\n6N5zE1d15iqq+I5GXciM3lkdAwnVJVu0aJHL4nRtoTAQ0UogWVGnD7rYpUuXzFSys5qh7YlkQ7Ra\nDddKHNRurbXWSuRXF4RyOo9qA3r7PpnfMS+22GKJmvpmIaPv1h0F+WxCJ1ZfffXM0rrf9AhbFaTT\nCXV3PsYQ6r722mspQbAmHWiLetxpREHhdDlhByjl3nvvneiGGaCdrr+xwz6wAcsxe/funR1fkMm1\ngnp+1mUGuckxrOyHP/xhMgVsCmNa1Cb4xg4z0ANOMi2//PI5RliTTjJrDKA4xkfGkUxz587NeW1F\nm/55Y4Zmm5vmMlpufMaMGZNjj+GSHO6lpkaFzFVU0UyiLmSGCLI+jcdsmDhxYmqU0aNHR0SR7egq\nWkHXjbXKuntGjx6d2Rl606UQWecOo8oCdBpHlhw8eHCiDET1fYvKeuWOIBsKqMXfe++92esLAXwn\nE8Mm7nSY74VEiy++eG7azsAzfgwu/gHUt0k65LOu9pVXXkmN6T16kr+tf8BqKQvt6UDGTdeuXRMh\nrHhznXUq0cx6iJ1H7dbLUNPfoDu0o8d5D74f6tOW7dq1S0biM6DsogJ6Yx5QtrZbEfJBZv8aC5sw\n2CwRE8Wknn766fybTrbyumlGn752pq6xPO200yJiwVZQ/CObUtDKjN6mRoXMVVTRTKIuZKZvZU/I\nAeU22GCD/BvHkBNs9ZLSgwwF5emgX/7yl4l6fmf7HLqURtfnCkGF7NivX79kE3p09RUvahN8COAY\noZ2s2qpVq9ylArJhD14jI9OAdprgxD744IP5Gsdv7bOdLqA7hxm6C+izzDLLJKLxBPSIYzHloOX0\nZCsd2nBwxowZyTL0G0NJfoPH10Buv9d/beuc2vdiaPwBvoGtmTAe51GzVjnng/5+Pdk0bG2Yb9iP\nVWE8nMUWWyxZIiTmHttuGNPD0DjVWMbzzz+f52j3FYzHijMrs+yCozecdrZ7y8yZM9P3wEgxnHrd\n7LpuZhRZbdVk1xx/9dVXZ11N+cUSMBcTLUUHGSS1+1p5yoWyhi1Yys+4RTuVatBVg/Lcc89lKUTJ\niEGhhFAbPpdpomxjQm644YY5BhYqSF7GxIIR5QzJxMV99tln06yqXVoZUdTvmTf2kVKLdRM5pyef\nfDKNOBPTMjo3VjlMTDeNRIHib7zxxlm/dfP4PpMeTTXpnbtEt++++2aCN4mZSMaUmWnLHGHsJbhl\nllkmj1UCcGMyjuzVFVFcK5SVAYn2b7/99jk/3PjKqDawMJ8lPPNPWW/DDTfMrZ0ckwTtupd3p5Wo\nmZmeZzZq1KgEAjIPna9KU1VU8R2NupAZzSg/lR5VeuCBB3JrH0vymCk2FEA70WuUGKU76qijEpE1\nYtjoTtZlakECJZNf//rXEVHY/yussEIiKcRkNjjm2kCF0TCNB7rH5s6dmyYMuq6MhaUoqylZWKRv\n+5ipU6dmCQyiMMuYKug1BDemfiYH7rrrrpQiDB6MZ1GbL0QUdBZSKd1Bwn/84x9pbHktyotWQz1U\nkamok61Xr16J6sxLn2UHSvMCUzPWzD6lqaWWWirlHXRDoSFnbZBgxt3n2EBy9uzZif7MN80aJMhl\nl10WEcWyTEsSfUaHDh0SYaEnVuUzzA+yR9MQpgB9jzjiiBwrstVTMcyZpkaFzFVU0UyiLmSW7djx\ntl2BhKuttlpqIFrYM5D87Cl/jBevhwbPPfdcajDWPISmu5lXkMJe1bSe0tQGG2yQWw/RMuVtVWsD\n8jGvfD50nzJlSjYwKGdgDRpLys/aqi0jRSzYuBDSGRMbNtBw9GX5eVbOhTHz9ddfJ7JCZAzEcZaD\nuef8mUjKL++9916yC+xKOclna6aBLs5VQ8ozzzyTpg7monlC0wiDjl7FSswlWvvrr7/OcXEcmIA5\nUxtQ1BzBUHg3bdu2ze2Xy8+V5l3YoJApyLPATEeMGJEMwzZAxpXBxQ8xNu4Z44yZtm/fPpuFXDNl\nXW2sTY0KmauooplEXZsTjBs3riGiyBiyOkRs3759/l9mLetsmZK2oV9krl122SVfI0vLlJ61pCmf\nY2gbIw4hvdq9e/f8Xq6vJgtZ+Oijj84VKaeeempDRIEa3svNffzxxxMJ6VpsRQkEqkFXzqitfV94\n4YVEYoxDqYlm0rTgM3kBvhNS33vvvVlygwSaJCzeGD16dKMVNxdddFFDRHHNIAsE7dKlSzITr3Ec\n9CAdTPtDZJ/VuXPndNc9YQNyGS+IpSXUv/wPTURvvvlmsim+hHZM86D2WVODBg1q9Kwpc8jY/vjH\nP87zM4/5KLZ7poMtlnD9MZNHHnkky2UYh8UfrhHW4jywTeVILKtr167pZmOA9LXK0JlnnlltG1RF\nFd+lqEszy94QS00TCm2yySa5YIIjLUOqCXODoaxllOqx6623XqKMTMxNLjer0MH0nzqhmnLr1q0T\nxdRTMQZZ0Ja4EYWza4EDB1YzwQsvvJBopNFezdVyTL+3gACq0oaTJk1KnQ1hZHx1XIjIVYey9CYX\n+fDDD0+E0LSgwQabKQd9yBGHHL7r1FNPzetL57sejtNWwBqBys9iHjFiRHoiHqXDVTb+v/zlLyOi\naJDB0DSVQOoHHnggEdLSWF5K7TpzoV7uXyhL47744ovJ3NTJXSOvxSbpW061BSVdu3bN+jFfwxhp\nNVXnd6xq42rVYtCgQTlXNFJxsb/tEUPfFhUyV1FFM4m6NPMJJ5zQEFG4rlBPpuvQoUNmMyhe7mby\nHt+r7qYtcqONNkrnkWuq8wn6qctCf/pX/VFH2KRJk7KbDDNQS6bz7r777tQjl156aUNEkaFpMgzg\nmGOOydq2GqROMs9Mpo0s3Le8zr8dO3ZMR18Hk2WTuqawCG6rujpdVrvggEana+l9yDFixIhGeuvW\nW29tiChQDaJA4YMPPjj1PYYDmVwXGg/b4CAbr2233TYdWWwHUvJG6FXHWd41ho+w/vrr59zRQqtG\nDgWvvfbaPMfrr7++IaJ4djfm4nM7deqUXYB8G8eCkTh/19bCEh7Nl19+mWyQC489Wmikj8HDHYwD\n/U23L7XUUslmobhjdm9Uj6epoorvWNSlmWUw2kh24uitueaamU1kLDqQNrrpppsioqjTCo3rJ598\ncvbC0sh6pmU99U8oRG/JbPTYGmuskc6rTjN1X11MtQGtde34PEg9efLkzKKQnmvrmH0Gh5Tu173W\ns2fPRC1IbGwgAVTx8DOLKbi6UGvGjBnZUWexOz+Bji0Hba2ZXyVAfbxFixaJxK4dPQ159Uqr++sl\n4H98/fXXeY08fI7epiWxLhURXoRzg/Y/+MEP8r21Cx0iCrZXG/wGet5YOoftt98+a+A0uGvkPFxD\n7rZ+duxn6aWXznHUm0AL8yLKj7BVq+bRqKoccMABeS9gte4d39/UqJC5iiqaSdSlmffZZ5+GiIVd\nNy7f/fffn6imW4drTZ+Ud1jUH6vu9sEHH6SzzVXm4nI1ucy+gwbSsUXjtmjRIrvDOMeOXS1vt912\nSz3i0S0cXrVpqL7VVlslAvoOnV/cUn6CR7fI+ljE3nvvnfqRxneemI4F7Wq0dK0eYigwfPjwRMcy\nwqnr3nDDDY301tChQxvtsMrVV3Xo3LlzngNPgobnTOs2c06cau7r5ptvnrqTn2IjCZ9p3GhJP/tM\n5zxp0qT0H8wZn+Xn2h1IzzjjjIaIguXoXffa/v37JwvE+PSJYw02LsQiaWldZU8++WTOEfNJ/RgD\n49VgPrwi56t7smvXronMfCbsz3LKiRMnVpq5iiq+S1GXZqYlyo8NtUZ10003TX2pdqf/2FpNmkEX\nFD0CIdq3b59IpR5r1ZA6Mt1LQ1oxRAeqpX755Ze5cQFGIKyMoe0iCi3oHGRuKPvSSy9lx5X+YCgG\nGR27FT06mrjZQ4cOzRVCXGk1YciMiVi/TRtynCHJ119/nX9z7D5TFaEctCjXXd1XzfWZZ55JlOHe\nqpHqIabxrSKif7nfiy++eFYnsAs+i7kC0aAS5MI+HMMpp5yS807HnHPl7teGMfTa8nY9Tz/9dOpc\n18bae3PVCjKIbO5iX/fdd1+iphVd5pfuPV2M9L6NE8138+Hee+/NbjHVC6wPu2pq1HUzaxVEAw0C\narTrrrsmzTMwKJqbdffdd4+IoknE5FIyWn/99dO8MeFQYhePmYDKoLJuCuWjnXfeOUtGBkYCsANE\nbdjcwAXwWklr1qxZeSO5aTXHa71jgGgmYQBJYv/85z/TSLJQAK0iH5hnJpubiJyx0GLrrbfO7zfe\nKLybuhzOiZmo/dAxjR07Nhfau4nJF8YdCuv4XX9jvdJKK+W1IoEYW+i01k83JrMR/VfCGjRoUJpF\njpUR5YavDWNWLkmRWy1atMjzYR4yqeyOY/yNqZtNcu/fv39ScBIAODgvy1sBH8OM7DDvF1tssTxn\nlNxclUyaGhXNrqKKZhJ1ITNEhCRKBLLohhtumNmT8SXLl5sZUFmGmSw7f/78pCC+T9MEgwJSalqA\n/pBDVpw7d24iItonM6JdtaEJAfKhfs7v9NNPz+1uIAozSBlNYwtqqOTjGC+99NJkKUohUJzB5Hwh\nhwzt/KDeySefnIxGdjeuDJ9y1DZjRBTUznGffPLJKRkgL6aEIZAzyj2ug3GfPn16LsrQwKPNVMkG\nYjEBLbyAWCTVtGnTFnpcjKWJzqE2sCuIWd7HrEePHjlmDE7GHfpt3pVbQbHKW2+9NccRyjP2fJ/z\nR7+VmbyePHvxxRfze4w30w7ba2pUyFxFFc0k6kJmqApZZDKIueeee2bLnYzPHIFQykkyGDSkrQ4+\n+ODcU5jRAqFoRrpUqxz9IrPRkZdeemk2dTDT6GqNLrVBE5WX4dUGlIQwSl5KMZoUlLAgEGQ+/PDD\n07SCWhptsBmtfsw7r6cVmShLLbVUfi+UwRBo43I4N+9j5GgQadWqVTba8AUYQMqIPgPL0dpK9+61\n1175HuVELbg0szZU7E4TDySzeP+4447LMpX5ZnMB13ZRwWdhJpl3v//977NZx9Y+fB5NL45JSybm\nYZ5vtdVWyVL4B9icLX/MA4zAWNHySlNz5sxJ04+PwcDFMpoaFTJXUUUzibqaRiZPntwQUZRqFN+5\njTfeeGM2nHP1aAmawe854VxGSLnEEktkGyMtob2NDqRxfDakgAxc8COOOCK1JB3IteUy1y60OP74\n4xtq/wYtuJtt2rRJDwAa0dW+h77kotLm2j/bt2+fzAZrUZ6xoERrqO18tadq0qlddmc5JGRVHqIL\nf/e73zVqODjzzDMbIopSlPISVPjwww8TCZUEob3ykuqB8hftSuPNnDkzS1C0JQ3pGmIGkNv1V3ZU\nHlpppZUS7TADpT0+yDHHHJPneO655zZEFE1K/Ahz5k9/+lOWFSGtMpLqCGSEnr6fl7Pffvvl8dkm\nCBPC/LBD5UVMlKsNuR955JFkVcpamJexqt1A499FhcxVVNFMoi7NLJvKLlCA8/jHP/4xs5z2QIvM\ny9vn0MNcX05lnz59EhnU/8qb6HGXOeA0DjTUMvfaa6+lA1muIUPU2pAROY4yNF3UsWPHdFuhKJ1O\nd2EHXHrMB4I+//zz2RbIJfUZ3G3na1wtCFAbp//XXnvtzPzcUZUGbns5jA09Dk2xnNGjR2ejh3FV\n/7bQRsUCijpnxzl//vxkEfwMCx/oVLVUCAqhoSCf4JtvvkkU9B4ISdvXhvH2PRBRzfjtt9/O1mH+\nhzZK71VV0NZp+18LPfbZZ59kbRDWVtKWSxobCz/0ZvjZZx122GGp/cteivFsalTIXEUVzSTqQmZa\ng07g8slcRx11VOpdmV+mkg25gFoFaT3O6R/+8IdEIFmvrJG0INqUwKJ5G6qrme6www7pkkMX7ZtQ\nuDYseoc00ERr5uzZs9NJtTFdudHe77EIrZle9+KLL+bGg5DPEke6znhywDEFr+M31HZ5cYkh3bdt\ntYu9qPvTlFjQPvvsk8inakB/c2Y5ztCIQwthJk6cmI4xBxqqYlUqI46Hq+55YjyOWbNmJVMzxhAU\nytWGuYFVYYJee8ABB6S+dbzG05jR5vwP7cJq4TfeeGP6OKoV2JXrbmy43FgXXazN9Oabb87zgeY+\nC6toalTIXEUVzSTqcrOHDRvWEFE40jpVZN3Ro0dn4zkk4mZCSxlZfZmTxyFt3bp19gRzSWW5cu0O\nmvu79/mO733ve+kYq+FCJFn29NNPT4g++eSTGyKKOq9apeb9r7/+OjM/d17m96/uLMiPqXCmW7Zs\nmf4A7azOrPMIi7C8Edpz1bGexx9/PD+33OPOXa/dhjYi4pxzzmmIKBDSOeqUu/322xMtoUj5IXsc\nfbV2uhsrWHzxxbN2ygnnVfAO1HD1Ixg3bICXsvLKK+d1h5zGFkO45ZZb8hz79+/fEFE4wZDTNV1x\nxRWTrWFynH1jUn5Os6qNz3jiiScazYna74PEKjHGFdszT/Qh/PznP8/5jGnxG8zdI488snKzq6ji\nuxR1aWaoBIl110Ddm266KbOoLC3r0UBQRlaUhTi3o0aNSheRduNm0mayOoSDJLKgFSynn356urcy\no84jmbE2nJcONNqJN9CmTZt0wfkHNDh9Q9fSirrKuLW//e1vszvKa9SdOeDYDKTGIvQ+W5106KGH\nZk3cGEDqbwtjZntX76vdvN+14RWoBLim0IimLPcbvPbaa4nIzhFTU11wbWlbHVoYheu2zDLL5O9U\nQPgWi+qQUhtXRcEQIOcLL7yQY8Yv8Dhh2hniq8xASF1cAwYMyC1+jIXtmMuPxVG/x7K8D0McO3Zs\njhVGpo8Dg2hqVMhcRRXNJOpCZhlNBuEyQrLx48dn/VXWozPoLhpNnY4jXbsZXHkDfQgFDXUeyd60\nDvSt3QAeisnQkGtRG6jTmzZW0B+s2yuiyNr6tn0nTUgDQlkdbhbLd+rUKV15dXq1Yj3oOsBshOBh\nA+qhKgPHHntsrlzCmqAYNlMOqG+Nrve5XieccEKiDG1uE36sA0OCrl7Hs/jXv/6VTMwaXY6wc3fO\nGBlWhSm4Fl999VUiFQZj/vmO2jC/eAjq1joTN9poo/RpVFJ8rmPiVNPtxkOV4euvv87KA9/GGJVd\na/Ma6puPmOFKK62UPpPrD80hs408/lNUyFxFFc0k6kJmKCprqpXJyIccckhqAQim51a2UyvUZQT1\n1EmXWmqp7NaRCWUm30t/crHpMlkdag4bNizr2uXHgHpPbdgoTw3cSi+90WuuuWZ+p2xNR9LO/tXx\nQ9dhD5MnT84OHzpKfdv4Dhw4sNGxcrvV2+nbH/zgB4nuatLYxKJWfEUUa5E5qJDM6++5555kG9CF\nzuaRuMaYEfTjRLdr1y6rFa4Z34GWxDqwKF6K6+K8vv766+zUMneM+aL8AV1hPh9zoW233Xbb7G1X\nW8cwXX9M0xz2WdZId+nSJbvEPNDA+PEPILa1AFx1HkrtwxetKMMYVAu+7Rp+W9RVmrrhhhsaIgpa\ngu66QF26dMmGEiaVyY8aaSJBvw2Uk999993zpDS+K1GhKEpiJhMayjhjlGyxxRZprJhw2hxRmXPO\nOSdt/4MPPrghojDCDLjjGD9+fFIiN4+b1OTVkIC+aslTLnvkkUdyUkh0qKgxMbm0aJblhnbKv/zl\nL7k5gj2mGEpKJAMHDmxU1rj44osbIgqDCIUVrVu3zgUIWkONM3OHIWThhZKKcx86dGi2UzpWpRzX\nzngJYwEgJOaPPvooxwWtRoeVSP/4xz/mOZ5//vmN5qgbX7z++uuNtv+JKEprzFoJEQ03Ro7xb3/7\nW56PRGNRhpKlMprX+Q7XVNLq06dPJkvzQBInSe64446qNFVFFd+l+K8MMJlNxmTy7LzzzolI/oa6\noE1Evi1wILUsOWDAgMyQSh8aCqCQ5n0mAnNBSUV5YuzYsfm0CxTRv2hSbVj4AG3JB2jeu3fvLIuU\nd5tElaEGBIJmjvmEE07IEo7jZ1qhoo4Zgiv9KYtB7uOOOy4pMdqMqkPzcjCtSBjfXbshAZTBBLTX\nQmClMrQay9GYs9lmm+XfsBzohsWJ8rOyMAzMZ/vtt88NGm3ZhJpje7XhPKAo2cPwXHrppXNuGm+L\nHjzzi4lrPhhvZdeBAwdm+VMDC4Q2rxhuzEqlQBtq1OxrnhJDKVT5alHbIv27qJC5iiqaSdSFzHQQ\nYa7MgeM/8MADqSlldyaDcpOSiVKVz9Tmt+qqq6ZGKy+kYCrRSr4X0smwNgLYYostsoFfqYKGZz7V\nhqWddA6jzeYH06ZNy2OjTZllsrg2PosjmDS08xtvvJGmk6zub8wiOr/ccOI46K0zzzwzEQ0z4IEo\nq5Sj3F7puLGQm2++OdGa76FZAquBxNATu/K6Y489NlkHVGNqeo2/GwNa0+8Zh++9916iNW/E9Snr\n4dpjo/vNFUh45JFH5hxUDrN8FWpCRsjvGG3k8OCDD6YXQAsz2Bi6TEwmKkYK/Wn6/fffP9/rHnB9\ny220/ykqZK6iimYSdSGzLCv70LLaE1dfffWFXFJZjWNHQ0NByGxz+YMOOiibEOhBZS1oSF/TGjQt\nRFH6mTZtWrq6UA3K0bK1AdXoLsjjyYrdu3dPvSabci1lUyUIDfU0oSaSMWPGJKOARko9MjF9570c\nXufP6d1mm23yM8pPpoC45eAiQz5ITUvvtttuOQ5abb3WOFjmZ9w1UJgPU6dOzXPB3jAI14gjbizM\nDyhfu0m8SgdGY15gCrXhfeaoiotti8aMGZOIrnEGikNb/1pw4Xxrn0Zp/pQflMArMUcxNdrZd2Js\nrVu3zqqBMXN9eSZNjQqZq6iimURddeYqqqji/25UyFxFFc0kqpu5iiqaSdRlgP3iF79oiChEPhFP\nsFuZFFEU7TU6MEeUFRhhjBsG0ueff56mGCNKi6g2T8V0RpEGBa+rfUqiNbnl3Ry85ze/+U22ytmF\nQxmD4Wc/q2effTaNPeUMJhAjzLH72bFquFl99dWzXFJu7NA2asy08ymHOT+lwblz5+Z4Oh/rql2L\n0047rVEr4HnnndcQUbQOMigdb7t27bL1lOHGvFP+8gRPzTVKgnqZP/300zQcvca4WV2kNZO557gZ\ncUyop59+OnetNG5WEzHzaveVHjJkSENE0XDEaLWeuWPHjvnder0Ze+akFV7muXng+9Zaa60sIyo1\nuQfs2c6csxpNa7ASncaVtm3b5tywcwtD1L0xfPjwJrVz1nUzcx4dmAHS/dKiRYtc2sgJdZPq/OH2\ncgq5mrq2HnvssRxECyx0j+miUW/2s2VmTt6A/uAHP8i6pj5b3ycx1IYb3Wv0euvrHj16dCYwD3cz\nISQAjfW60nQCqRnvvvvu2cmk1q2erkaq7swBdgNYLqh7bsCAAXnDSXxu4m/zQkxuxyuBqK3efffd\n6YjrGTABLVqRLC380EmlA+zOO+9M19rckFQlCnVw52KTQze3zq2tttoqbxQ3uI5DY1obkoe5YK66\ntuuuu25unKf3wZJT51neLlqN2GKgli1bZsXEGFicwb22GaTPtF5AQuTev/jii3mtJG0JTZWoqVHR\n7CqqaCZRl5t90UUXNUQUvbFQVu9sjx49sv6GmkAKNTrbx6BVaKra36OPPppIBaEt21Nf9B0oLHSB\nkmp/06dPT+qiu0fGlzGvu+66pDBjx45tiCi61NQXUdjZs2dnndp367lGjdEq3Uper1No0003TbSw\nkB3DUIuEVugkCowGGp958+YlQ1DXRv+gepmi9evXryGi6HNHs1H4bt265fliT6i8mjQ0IqWcDxY2\nefLk7DdwfbEdn4mGlq+pbYV0SO24447Z7y7QUkg2ZsyYPMdTTz210eNpMClbHs+ePTs7BtF2PQM2\nXcCqzFUsxlh/+umnOY8wPjVhD2wnwzyy1jxR09aJeOCBB+bnkitlmXXWWWdVq6aqqOK7FHVpZshQ\nfhg1c+PNN99MHU3n0NlW3jAMLO6XZRlk8+bNy6xK30EZj2WxMsXG5np36SUL0idPnpyZELrTyova\nYNz3OWZGj+y7yy67pDlBJ9K92ApEuv322yOi6LeFvhMmTEgEcz7Qiq6yGYGHiuvyMs6++8svv0zk\n16UFVRb1yNqIxp1HEYWm1W12//33p1aEJh6UrlPJunLXjC8B4XbYYYe8Bq6dcYL69DiPxdi7tv6+\n3HLL5WeYbzqlXJfa8DudZHq96eMHH3wwUd958gCsJ7DGnjeDVfEMrr766uxKc711CzIWjZXNC4y3\nTZqenqYAACAASURBVDlsQPDZZ5+lNmbE8Ujcb02NCpmrqKKZRF3IzOWzsZsN5uiudu3aZU8qlOFE\nczFlHRu6cyQhy7LLLpuOH8TFBKA+tIX+tAWdqkTy1Vdf5WvKDwiXWWuDAwu1lSi42ddff32iP31l\n1RQUt0qMI82B9b3z5s3LFVX0dZ8+fSKi2HIGItPs9D1tKquffvrpqZ9theO137blLh0IlazQopm3\n2WabvFbcc2hvvS3mROfaxFDf8brrrpsVBRpS6LOHlMYJQ1AGxGwOPPDA9DuwOsxpUQ/Hozchve2J\na1dYufYQl4OuooL5GGe9587//fffTwfctTR3ILXrgN1w78tbQ51//vk5Vs7PFlc8qaZGXTezQFNQ\nVpRq3333zYFHCd1EaJybGZUxyS36f+GFF9JcUEIwARlGyj0uhj26GEhqeBtttNFC9V83KhpUG4wz\nZo3atFLB0ksvnRPWRPdaN7GLzJyRzNDJbt265Z5PTBKbKqgf25zAZ0lOJhPT6KSTTkoq6Dw32GCD\niCiSjD2hheNFid1EEnKvXr3S6DLJ0VsTlWmqLEZ6MBtfe+21NCWdk+RhkpM9Ji4poURmocTIkSPz\ne8wD5pExrw0GoPnl6aO1u6e6SSzc8DmMMU8hIYdQaFv+3HfffSkDygtXbNzgPrCPGjMTDT/nnHMi\nYsFOsICP5DTPv22DiW+LimZXUUUzibqQWYaS/WQ0NOvRRx9NNIWWDBr0VBbSvSUjQ52HHnoov0fT\nhgzFKLBlCysfMvj7fvvtFxELMhxkKJdXLLmE5hFFYwE0Q41k5B133DFNCuUjyIYyW/LnvEkG57/S\nSislKinPYC2QAIpDCGMGEY3HhRdemGip0QPiQvNyOH7HBZ00ObRo0SKNHo0oTBznBF3QQ5Teue+1\n115ZJnQ8urjMFY0fzD/jSHKgy1tuuWWaixAac8NsakOJzlJIzIgxNn/+/KS+TEk0mvTDDsg3bAer\n6dixY26A4d9yFyKDl8xgdmIm5s9FF12U2xGZtww+jS9NjQqZq6iimURdyCxjMC+0bPbu3TsiFqCD\njMxkKG+T4j22ZIHQUHjffffNjA8pIRf00EwiuzMslBhk57feeiuzqe+DItCxNvTsQmSGFONt0KBB\nmYG1bdpax+dqHmCMOH9I2bJlyzTPnCdm4TMgBZ1nbHwGtLvkkkvy6RvMsfITLL/tHBkxtLVy06qr\nrprjDRmUbPyeV0IvQmTn8/e//z2RCCNhWmnUoGltosC85E/QmB988EGyKNcdm9KsxKCrHSNMidFU\nuz0zsxIyM1QZnYxdZp155rr07Nkzt+Pl9WjRxaZshuBY+S/GQeNNu3btsikGU9O0VN4G+T9FhcxV\nVNFMoi5kljU5w8pQ3OWnnnoqt/yRgTSpcydlYO+FRhCvQ4cOiYQ0jAxKU2rap+1kR4jMQT/iiCPS\nkYUe3HNNFdzGiCKby/jKNtB33333zUUdGikgGp2vbRAyKrFgCL/97W+zMULmhQzGhOOOzdD5UI3r\n3r9//0RHLYHGyKqhchgHSMVVVf77+OOPE+2xJg4+p9bx8DvoXtfplltuyWsImbnWGn1cu/KTLrEO\nlYrtttsuf8eH8Vo+SG14n1CSMmc22WST9HogtOthbJSZOOHG29heeOGFOb9pfKiKJTg/etgctcGk\n0tn555+fiy5UNcoPVmhqVMhcRRXNJP6rphEtilxfzR2PPvpoupXcUu109KwNxqGe2iTt9s9//jOb\nJWQmtWmaXaseBKXlsAJZslu3bnmMnEJoqKZXG3QOR1IDgxruRhttlPpJnVpTAqSms2l0WdaWqx07\ndowhQ4Y0Gk/6EgJp5zSW0BP6c3VHjRqV46auq5FC+2A5NIRgFFoGtVu2a9cuqxVcdE6w+qxGD+wG\nonGZe/bsuZC+9z3GlDOPqfkOLEUTzLrrrpvMzzhwmTGp2ig/Fsemj7WbAvJ4+BsqAXwEfRP8B/OP\nZ3Peeecl0lv26XvpauhPW/MTsBeoP2zYsKzO+ExMABNualTIXEUVzSTqWgI5dOjQhoiiu0k2giQt\nWrTIDARVNclzJ6Gqxdy0gzrjhRdemG4pxIdgsjoUsXG7ziC6hFP48MMPZ+bkUKs/2oK1f//+ubzs\nsssua4goGIBOI6zilVdeSZ0GAR1beTN5WZ0zajH71KlTs3uI9qONIZD6KZ2NRUBmzuj++++ftXUO\nKPeWQ37xxRc3Wj7Xp0+fhohCu6r/csx/9atfZbXCZglYDQQuL2zhQ6gHjxs3Lo+dZ8AZp691lXHh\noSTGYF727NkztSpX3Zgb4yuuuCLP8bDDDmuoPR/zDTLfe++9ySz0NkBCtWGVDhrWeKt9n3vuuela\nl8ek9rE6EYWG9x3mlkpFx44dcy5ZuOJn86GpO41UyFxFFc0k6tLM+nfVWDmmEKa23qfTiIvN+aQt\ndW9xVemFTp06pYahd9UkLXwo1+Egsr2qIPjTTz+dmyPQgTpyoHltcNRpwXLv9J133pnZk+6Vxbn2\napW6uJyfMZo7d272XAva2PlBLw4wZNbTDVk+/PDDdL6dD2YAGcrBfaXtXBeatWXLlumMq5FiQpDM\nxgbGgD6GTj169Mgtn+hPaG9hDfalQw/b05euFv/pp5/mXIKGdDXXuTZ8vvHmL/BR5syZkwsodCti\nAVgUz4TuxSp95oknnpjsD/PAzHhBmIlFMzwTnor+60mTJuV46rnHVnxvU6NC5iqqaCZRl2a2JQsn\nVy2Vo/vKK6+kfqbF6ChOsZqt7KpmydV+6KGHEmV0gMlUHE79yDIoN5vupocHDx6ceotGs50R7Xzg\ngQemHrnwwgsbIop6ovpfbQcajQ/ZRPnhdRiBY6G1e/funRoTWnH+LSk0NlBGP68aNgS58MILs2+c\nvlIz5fTeeuutjfTW4MGDGyIKr4K2xAZ69OiRSMEJhtr0udot1gGdoNXIkSPzc9XGoTjnVn+B3mbd\nVur4Hpn74IMPpu9iHIwTdK/dnXPEiBENEQsv7IeQu+++e+pXSM/dFuas5bN0sCrLpEmTssKBjaik\nmIOuHYbi+mCqkPyqq67KLajM8/KDGW+44YZKM1dRxXcp6tLMMmF5sbwMctddd2UdDULg/RxhDjEd\nCsl0Ga200kqZpWljWoV76fvoE2tJMQXOaLdu3RIRZGobxlkHbIvXiMKBhxY0DJ3cs2fPzKh0pbHQ\nH85Flt3VUSHNn/70p/xOGZ+z6XwcM92FzejMUsPu3bt3/s0KJ1l+Ud1REQuv6/aZ+gEOO+ywRB3X\nDCPgAxgXyK0zixN9yCGHpM6HMlZe+dnjUT1WVfcel523MmTIkNS2+huwKj5LbVgbwPGGuryC559/\nPuu3vBY1X92C5Ufr0vEY0ccff5xzDuPk85SvoTqz3m3MBGPbc889k52aO+rZOiCbGnXdzAbcBGVS\nuDAff/xxTkx7fhH6LqIL4mKhoybXPffckwPB+DKpbAjAGNKkgDYppaCFhxxySA4aWuxCuUFrw/tc\nKEnFMro999wzGzxcWAlA6atseDG1NNMPGjQozR4Tz/gxXJQvGIqSqAnqOzfZZJMsBTLiNEtoxSyH\nayjZoIUS56WXXprJxvEoK2lQYZqh+M5RQrn11ltzkjOpLrrooogoEpObzHXRmGHclIOmT5++0JJU\niX9RmxNItsbQGFv40qVLlzxnSVsClOAZvBKSRiFG5Zw5c5I2K5cxAS1kca3ICTRf6VAzzcMPP5zJ\nhXEr8aHwTY2KZldRRTOJupCZISCjQVDZdfnll0/qyFiDbuioUgHzR1GdcfbZZ58lnbaAG3qjLJrz\nGTIWKEByxsZpp52W74HIsqsF6rUBtWoXX0Q03n3SZ2tttC8yiinro4soKXr17rvvZmlEiYnRp2yB\nXkMrmdt42JLm+uuvTxRB4wXzrhw+C0KMGjUqIoqFMQ0NDdnEAk0t1seInCtqDjHR1RNOOCEXWrhG\nyltlEwvKYxTQH7J++umn2VbKZMRsoHhtMDihKbPOhg5du3ZNWmsuMPAwIUwEy8JaNM8cd9xx2QSE\nzRlHLBK7M3c0nJCX7p3Bgwcn42S8HnPMMRFRLAQpz8dviwqZq6iimURdyEwPWNalVVJ2mjFjRpZZ\nZESaQha3AEA7J61BW5xzzjmZKS3sZwzQhUonDBklKiUt2nnatGmJOBpBaJdFPZUewkBV+ss5RRSZ\nl05kFsnyUNW/vAFIOHDgwGy+seiBNoOIxognAFUcH4TccMMNkylADRq69iF+tWGcMSIGJSR//fXX\n8/MxMcv5aDoIwmTTGGLp6YgRI/L68gNo1ponbUREobPND/NBk8fYsWOzeUW5hx6H3rVh3jE8tZwq\nCW288cb5zCiLU8wFx4Yllp9lZqHHKaeckqVU6G3uYTPmjDKjhiRGnJbevn37ZvMVtqjxB6tsalTI\nXEUVzSTqQmZIImQ7yLLddttlGYF+gojcbP/Si7Ii5Bo8eHDqJw3nnE16nO4qu3+QCyrOmjUrtRkk\nsBndopZA0mDQBAOAxp06dUrtCx0EHaullANtuZ7S1cyZM/NzoWN5y2KlJ+fP+TRGzuHOO+9Mnafk\nRBNzW8sBTeleKGR8brvttkR7x64yofEGetK3UNW/J554Yjb4qF4oG1rM4MkOSpV0o+YVlZLjjjsu\n218hv/FxPLXBk6FR+TkYy7LLLpsoaqM+7jg0x8hsJIAhYqBt2rTJOVg+D8soeQTuB9UP1RX+yJNP\nPpnMkmfj/HgDTY0KmauooplEXcisdgltZZRaRNTWxhGUrcvPI6K3LWbg2I0ZMybrqHSgTElTQDna\nQjup76xdXkkjYwqWwmkzrA0sAbpCO1n2xRdfTEYhm3uP74QANi7k2qs7fvTRR1nX5MJzxOkrzILj\nqbFCG+spp5wSEQv0F6fVQg9I6DuMnYDclgaq9/rOfv365ZjR1xa0uN6Q2WIOn6V2/cUXXyR78Bo1\naW2+fA3fgYVwco3jPffck+dgq1+IrHmoNvgNGpo41/oKLrjggryeKg3q2PwDWpU3BHXN+5EjR+Z8\nMlfNZz0PkNc1Ky/iwZAeeuih7MWwcYfqASbS1KiQuYoqmknUhcyyGwRUa6Mf58+fn+1s9Ag3EfLK\n7lxMmQoaDhgwIFGOU+xvNY3nEVFoaYsKMAQO+ltvvZWOJV3KGV7Utjp0HdceQtnq9eCDD85WQotN\n1LYhIp2j84n+537Onj07dZ3PMlbca/qVRobq5U3ifvazn6WzbCwswaRZy2GsVAgcv3NdccUVF0Jr\nrbn6C7AR15DbrLa86qqrJrqoOKg367KiOV1bY+w4dBJOnjw5W2fNIfOO+18b0MxYQl/nMmLEiGzP\nVPNVk+ZEc60tvaS7OdRnnnlmuu28B8jruI0rtuW8sBfsZtddd817AJvRZ6F7TUXkP0WFzFVU0Uyi\nLmTmEOpykv01qG+yySaJxJxnPdeWj1lOyIWVSWXsUaNG5VI6y/QgJjT0/TKqbGfRBmRu3759vlfm\n5z4uyglVV+VeYxlXXXVVRCxAM1pZFxqNxKWHNBxJesuxr7TSSqmndQ3pbFLftpCddlMzVv+lpS++\n+OLsHsOWuNjGohzGA8rrjLMAZe7cuakzfRb3nYfBkebc8hag0ssvv5zIrwICXWhZc8m1o5V5EvyZ\nnXfeORGxvFn8omrpjsn7na9a7gMPPJAsiVfh3FVnsB1ja0GHrsa99torKx4cbk+QxEiMEfS3oIVb\nb/FKq1at8nt4E352HZoaFTJXUUUzibqQWd+rLEdbquW+8cYbmQkhE43MRebEysA6YTjV77zzTtY1\nOZpQh9tn6Z0srOuHxoAg48ePT9Sg8xwPJK0NKELL+n46+KOPPkoGobYNYbjHEJGbCYm4za1atcre\nbE5/+bEkxg6aYQb0t5rlE088kXqVruZ860wqByS2BRAXmT8xePDgXCWGVal/Oheo7rgtgfT77bff\nPlGGduQD+Ey6XL1f/Z5OtfyvY8eOWZvlZvM7uOi1Yf7R7+WH9H3zzTep1y1bxK54FFZ2mV/lZ3J3\n7do19S20hrTmDHbn+pijatYc9G222SaXPGJePmtRWwn/u6iQuYoqmknUhcwQQ9bl0Mk+a621VmY5\nGV+W54TS1xCZQ60v9vnnn0900YGkn5XGgeo6qGRJNWyacsyYMYnEupWsRNGZUxtqnlCBA0vDH3LI\nIXkMHGX6V/cYBIam/o5dbLfddlkVkPHpLDqMRqS/oT5NZ2wPPvjgRJmhQ4dGRIEI5ce0CAgBGa1I\nslD/H//4R7q9UA1SCdfKemJIqVd6+eWXz/PlFWAZarnGALPxs89Wtx03blz2IkBmiLyoVVN6zM1V\nmlxd99VXX80VZqow5cfO8iw44M6Ph7PMMsvka1VWMA8sxnWHxLwh46KqsvXWW2fNmneCWfrMpkaF\nzFVU0UyiLmSW1aGclUNWAU2ePDlrqNw9jiwtKfNyhWVQmXObbbZJpOUA6h6SrfVkQ04uNETmjF5x\nxRWJVP6li+lr7nZEkak57R5/I7uvssoq6RNgGpxRGpq+xgCcP0245JJLJvL7LKuB1BvLG7gbK6hD\nS6277rrZ/cbHgDq642R5ob5pHXT5wWq77757jrvavFqp6wIR1X25v5jDrFmz0s2miY2Hc7dtsN9j\nA/oCIPlnn32WK9Jcbz3UPIbaMM/0VRsX2vbll19OjaoGricAMvImyqu0jMecOXOygw2LgrTuBeNv\nTJwPb0jFZcUVV8y+CsdqHTsm0tT4r2i2GwPNUlJp1apVmjp+h0K6aOin7XfcTOjI97///TRpDB7z\nQikMVWNYaCGVZNwURx11VLaR+iwXys1cG24E5hV6jwL269cvZQM54UI7b6aJG0+iqX2yozKZJXYo\nO5ovsWlEMEbl5XQTJ05MKWJiajj4NvOEmWSSMc4c59SpU5MuOx4T14Q1/sxMyxuN9d57750JWBJj\nyDExLd7Xmus7XCcyaOzYsZlw0FFzRbNNbdg0QhONG1KpdOONN07DVkJx49kOS0JgmjL+zN1nn312\nofKV6wvMJHuGnITMECShXnnllUxk5pJlu2h9U6Oi2VVU0UyiLmSW0TQRoAey0MUXX5xZxRY3jBYl\nIjQUGimuK9esttpq2WCCkiiey9CW7WmYZ6IxHVC8mTNnpnmCDpX3za4NaKElEgLJ6gMHDsySDnSA\nbEwyjfXoN0qHsg8cODBZiSYLcsXPGAKKysyCuljO97///Vwwgm5rSoDi5UBRlZEs9kBl582bl1QY\nzdOA4TXQz5ZQjDsy56677srFEViIlkjmHYTGetBOSyHJoY8//jivp8907TCF2kCnIR85Qbp89dVX\nyfyUr8xJSA9lvc44GOvNN988rw1WApGdH6bDTMM4HAcWufbaayc7Ya5aTlstgayiiu9o1IXMsp7s\nroSkQX3TTTdNVJFVoI2fZSFZXlukhQotW7ZMzUtvQBlFe+UmSA1RZVKa86233soleLI4lKd5NO1H\nFLpXAwU0wUA+++yzRFgL3JkVSkQ0OU1ND0GvpZZaKssUDCXZnZ5S3vJe58Wgoe26d++e2Zy+YjzS\nrOUoL/KgvzXi3HHHHVmuwirKT/3EWCC2v9tcYdasWWnuaVmliRmgtLv5UV4wUtviiBn5fq+xGeCi\nzq/8fHBLFdu2bZvz2CIMJqXv0bRhjMwvrGHevHn5WiVB/pHxN88s+GCMaRFWzr3++uuTPWIErp0x\nbGpUyFxFFc0k6kJmDinEpFU1qrdp0ybbJLmXdDY9ookA+kE4OmyZZZZJZFZi4tjKajK0copCPISQ\nUTt06JDL52h5r5Hda4MDL8vK6o7n448/zgYKDMR5QVufq4wiy3IqhwwZkv+H4hDNecjINhLANKAB\nhvLJJ5/kQg4IYIy+7QmCEE+jRPk5UiussEJqVG4uVIF6dK7j86/50aFDh7zuzgXLUAbyHp6DigW/\nwvLGV199dSFdba64PrXhd86Tr4IZ7bXXXgs9QxlrKC/gwFqwR0xwzz33zPIo59vcwcjMQfMCi3Be\n2NXcuXOzWmFeWEiketTUqJC5iiqaSdT1FMgqqqji/25UyFxFFc0kqpu5iiqaSdRlgJ177rkNEUWJ\nSlsnk+mDDz7IYr+VJlaRKOIzH+z0od9a6+DMmTPTgCnvGsFMsWLF7xk0TB8tfJ9//nkabVbneFqG\n77388svzQdYeJq+8wMxiMr333ntpTgjf7XwZOgwSZqHXffPNNzluZRPNmFj7bSyVvZyfNb+dO3fO\nY2SeMGmUeoYOHdroQd1XXHFFQ0Rh2Hid7/r8889zNRczUyuiEg2TR9unvcCYm4899lgaXd7DcHN8\njEG/9zoGkfc/99xzaaxpnjEPNGKceeaZeY7HHntsQ0Rh7Gn00JjzxRdf5Pi5JhqJyi2wWnKtHlNK\n7NWrV84914pJam66ZuX90pTIzMe2bdvmOGt6YvCZxzfffHOTHrZe181sgNXh1GFN2O7du2fzvaVh\nLrhFA+VapaZ9j69s165d1kx173Am1T85t7rG3BwSBde1bdu22b+thqdGzk2tDd/LiTTR9T0ff/zx\n+agSHV/qpMaC8+57bW2k3/udd97JBGMsHK+JzMVUG5eAdMtxWZdbbrmsuevG8tkmbDlUGXy3zesk\n3e233z7dXJ1gHFndYhbRc9kt3rDY5Isvvsi+djepm1d/tcX5up3U2iV1137KlCm5iYBzdWO6CWvD\nTaxPXPVBXfuNN97Ivm/zRTefKG/M76aSrDp06JDdYwJYqV2rOBg7vfA6wySmMWPGpNPP8fbZkmhT\no6LZVVTRTOK/2gQfZUBzZKVu3bplfRG6QW0P8NarW96qFup++OGHCy1Ul810j6H5tmiB+uq26Orr\nr7+eGbn8YG6IURuORaZ2vjrdfvSjHyU6oJp60GVzrAW6WqaHdj3xxBNJ7yADWk+u2PTQFkXOy4ot\niPSTn/wkF9BjEajgty2f002mpm15p3P94osvkgq6zpDaY2swGDV7PePmw6qrrpoyQ28y1MEArFpz\nPFAfY9ARuPXWW+eqJv0MGMOi2JXPQ2/1sdsUY4sttkg2aH7prCPrXDtzxOoq1+Orr75KauwhB5gf\nZmrjDgy0vKwR/R8yZEiyJeeF1SxqZd+/iwqZq6iimURdyEzs07c6l2jX888/P7f0YQhBZihktYmO\nI0gOrZZddtk0day4ojtoGPpKdoS+ttfR2TNhwoQ8Dl0+MiRNWxvMGVrFCiif26FDh8zetJmVQjqM\n9Jzr+aaNIMOyyy6bGd7KJZrQairbMkFkWR4KQ62nnnoq0cqaW0jLTDFWwrXznbSrVWwTJ05stFVx\nRGHWlB+WhgVgTLTegw8+mJ4CDVzeIsnKN4YRlPQvn6Rly5ZpCPFhMAW/rw2Mz2tpV8faokWLHL/y\nNdKfrv/efLDFFT9k6623zuPDXsodj1gMk5OpS3/rSBw5cmQyGt1kxtMca2pUyFxFFc0k6kJm2Z/u\nsapG9t1mm20ym8vidBVNZwWUDKW/2gbnZ555ZiKtUgFU56ZzKrm/UJ5O9+/mm2+ezIAD7r0c8Nrw\nN5nYahYa+pNPPsl+cdmcruLwKhFBdaUsrn6bNm1Sx0EvrrB+XfrL91tF5e/c7+HDh6dvwC2nuxa1\nC0ftZ9CwrpP+46lTpyZCYF7YBtfVmNKlVkZhQTvuuGOOmVVFfABjjFW5tjQz1gLhnn/++dTzNpS3\n0Z0147Vh/jl/c8Q5tG3bdqFtf20xVPZReDHKdo69devWqeOhKjboQe7mqvMw3zAEbGebbbbJ+cuP\ncc8sajvofxd13czopotoSxjU7uabb86T0/COKjKKmA+WgJUXImywwQb5+SYTSmZyKwO5YJYoojRo\nyqOPPpoJR6kGvXED1QbK5/uYFGj+4YcfnvTVRHCzukjlY3YRXdROnTrlayQYx8YccTGZR0pUkptx\n32yzzTJpSIrKLt9WmlIiYdip2boJhg0blscuQZBG5dZf0oJBSW5dddVVeROjoeSJeYAqo5/lZY1o\n67hx41ICuOlM/kU9L0x4jyWiSkaXXXZZLkYxdoDE3mfKZ25MksQYnXrqqblBhySO1jPgbNhhnqtZ\nSyro/0svvZSlT9eOzHG+TY2KZldRRTOJ/+qJFigFVEKp5s2bl6UZ26egzMwKP2sKgOAQ9JVXXkmk\nZ1r5m9KNDOrphEop3qdc8PLLLydCyaqeFMkoqQ3lJuUFGRvq9erVKxFYpoUgkMf2PZpLmCbG6uqr\nr84MbINC7AVdVapC1VA61N4Ghi+99FIaMbajMVZ+r3tJYBuOm2Sq3Q3T+ZIbyoauB6POeKPKjLvu\n3bsnFSclIJatf5SgXDudc0xOBtKAAQNyHDAz71WqqzUzlYKMO8OPrBswYEBKJayQBFRGdKye1GG+\nM/F69+6dY4RhYCVQFiMjY9wjzEMm3JJLLpks0T2BYZqzTY0KmauooplEXUsgjzjiiIaIIotqlaNZ\nO3XqlBmZePdaWwsxy7yX7oJk77zzTrZAeqK87EePy1yyHhSCFDL2xIkT0ySRKekQWmbcuHHZ9zp0\n6NCGiCIzaxvUrtiyZcvUWRBFKQ7CYQ1QF7qLtddeO0s4Wks94xeqQB5jxbCRqZV3Lrjgguyxlt0Z\nSZC3T58+jfp6TzvttIaIYttYurx2eyfH53iUJHkRrof2TQ1BELR9+/ZZMtNeqm1TM4leZoF1QFBI\n1qNHjywV0vuQFZs47bTT8hz79evXqDcbq1CG+vGPf5xPt+SF0KjmIMNL6ZDP4qkfhxxySF5/G3Tw\nkxhu/BDlLRsYmtuM4AMPPDD/X94eydjVnt+/iwqZq6iimURdyGxVEY3BVYQgu+yyS2YqmR4iyn6+\nT/lIY4imkUsvvTSbI8obuiuN0eMytfZNyECfr7feepmRlQK4yn6uXVVkVRiHF9r6vM022yzPg2a2\nLTBWoIwEdbEG4zFjxox0MpWJaGSoZWGF3ztW42A73c022yydbdqY84otDRw4sFFWHz58eENEVLGZ\nJQAAE3VJREFU4b5jFhZvvPvuu9nq6RywKwyBI8uZ9tQMjOa4445LJ9x4cJ7pQteKh8IXsJgEK7j2\n2mvzvbQrtoVdXHPNNXmOp5xySkNEoe95MljNc889l40yEJ+OV/LTngy5IaaVdjfddFMeH79DmzK/\nBbMwzrZo9j73Rfv27fO9nn4KzbHAe++9t0LmKqr4LkVdbjYEpiE5o5D0kUceyRolDSE0j9MwUAfS\n1T7XR4sktLDRmnombQPBoL0MyhF98803s9FA9oMiUKU21EQhMTTVLPH3v/89z5XWh0B0L61GZ6kd\n+7dv3745bpxNCwa43OrMasE0q4YQbvbtt9+eusoSSKijHl4OzftQ5rzzzouI4lputNFGWZt1bhDX\neNt0T/sjJxeCzpo1K3Und9f1N8aaQ+h/rrParmrDbbfdljqTmwzdF7UpI4aHVegdMDeGDRuWNWDn\n6TE7qhkYGV/H/KKD+/Tpk70O5ojrTlc7Rt4Axmqczem33347r6e5ZYzUypsaFTJXUUUzibqQGWLR\nI1oJZcEBAwbkk+zoW7VBXURcTgguq3Oml1pqqXRmaUiLBSAEvSVT08xqixzFPn36ZGcZpKDRFvVs\nX9lVuyVta3HG559/nghI73J2ucqyq8+HZurAa6+9duoqTrIaNU3o/Lj26qGyu26jXXfdNWvqxg8S\nlJmRwKroQZrSMsDjjz8+u9u0NzondX67g5SfJIld3XbbbVnfp5npfq/lt3CMoawqQ+2OLsYFi8PY\nIFht+BxzBZrSw61bt845qT3TWEBVrMo1NO+dywUXXJCeD6+itmMtoqiouGZ8BrV4TGGNNdZIv8A4\nW2zimPkx/ykqZK6iimYS/5WbLavqmNG5NHXq1NQSmvXV9GhUaCqzaaJXw7zmmmvStaVD6U3I62e6\ni7bgwkLJJZZYIjuJfJbaNX00duzYdAp32223hohiccABBxwQEYU2POaYY7L5Xh1ZFlf7hCjqkPrH\nZd9HH3009SCk4zz7PUR07HqzsRhjtv766yc7ov9ssGB8x48f38gJnTBhQkNEgUKOmzvfo0eP1OE+\nQz2X/8AFhvJ0OMYxcuTIdL5df7oUuukZMJcgKufc8YwYMSLnElaHqRjT8847L8/x4IMPbogo2AO3\n2XX7/PPP8/3lmrAeCSzFw93MR0zp0UcfTXaqF8GY8A2guWvq/PgvxniNNdbI6pCecEhsLu2zzz6V\nm11FFd+lqAuZL7roooaIopuHDqVljjrqqMxIMhQ9zWXliKsR+9nrRo8enYjQr1+/iCicPw6trE3v\nqd3JgrRGq1atMgvbCsbPUHH06NGZ9caNG9cQUeh8uou+WXHFFbOTh16ktzi8EB9acarpuzlz5iQS\nqEFOmjQpIgr95aFnvACvwzy4sR988EGiNxYB2ej8++67r1FWv+OOOxoiCrTBQly3OXPm5LWA9txW\n6GJVm04xXgPnePjw4amf9QroiS+vknLOND6d6sFr2223XbI515sDrid7t912WwiZXWfeDWYwZcqU\n9GCwBvMJ8ppP3mv5qn7sLl26pK/j+C1ftH7B8ZdRnbcBfffcc8+sSaubm6vYy7HHHlshcxVVfJei\nLjdb/ZPbpv9al5XsE1F0s9BZ6pn0p84oG+1xkKdPn56ZCpqpO2MCnGTIDVV0+XCDX3/99ewWopm5\nvVb+1Eb5Adr6hTninTt3Tk2qH5kX4D1+dl5YBo295pprJjoZA5rQ99NVuoTUaDEFq5k22GCDrIGW\nN4FQTy8HtKEhMSi6fcSIEXlcNjKEIh7yZ6MBdXK1YaygtmecttRfwEuwxW/tQ/lqfza3TjvttNTi\n2J1+A853bdDxzo/zrf+5b9++6TyX9xrXE41V+Nf1cYwdOnTI8+JaY0L+5d6b97aNshkiRhVRbFOE\nARo7ur+pURfNvuaaaxpqTwqV1IL3/vvv54X1zFvtk6gvymypoJOTCFZZZZUcPBOUWYCClfdIQm0Z\ncZorrr322pzcGgDcSN47fPjwhZr0NWkoK2mZnDZtWu4c6nMYLOXN252DY9I88dxzz+UEE4w9k5YB\npgXQNUJ7Ld5YeeWVc2GFcpVEaAH+CSec0Iii/exnP2uIKJIMA811uueee/JmRY1NPK23KCUDVCIw\n7i1btsybR1MFKuv3bgabERhPpRyU3XnWhtKZMuNNN920UEsuGSV5HH744RGxQKo4d2MkObjJyRw3\nuZZdCeaAAw5Imu13jh9ImF/otvtBaQowrbrqqvn95A15ZawGDRpU0ewqqvguRV00WxkG/fWv1sY2\nbdrEvvvuGxGFSaIUZGmgRQKsfDSEmTF//vzMjOgz5Jc5/R7tU94ob0Cw5ZZbJu3RtIG6aFqpDQ0g\nzBnUSGno9NNPT4rr/DAReytDLceCTqJSq6++eiKxUoQWRGaZdkIopUTB+HE806dPz5ZL7IV5IvOX\nQ3mn/DgYn3333XenEWPMMCQLXKCqRR1KOFDqV7/6VaK2xh/mEdMM6rkeTL7yXmC33XZbGnAQ0vVh\nENUG48v5ae11nvfee28yIFv/OF9o63zJGm215M9OO+2UUk9zDCnkOmg4Yngx7zBTTHTQoEG5/xpT\nGJtB85saFTJXUUUzibqQmS6j+SAKDdK9e/fUMzSDzAyFZC66QAMINL722mszezNgmE70FW3GAFGq\nwRCg7kEHHZRZ1fdCl0VtyaLZ36J7ZQflhRdffDEzPxSSVWV+popzgKI0e4sWLbKxhtmD4dhySSlG\nWUfThs/S3jhixIj8HsdD31tIUd7BEvr/P+3dPWgUWxQH8AETUEiEICKIZqNRQbEQ1pQSBUGEYBEs\nU6WxsJIUAVtBV/CjsLBUbMQUKhhBg1jZKmKrgiyCiBgRbQIKr3j8zg43eb5s95h3ThNck93ZOzP3\n/3H+946FJzSeGOLIyEi0uTAT2p0hR/85fppZEGXLli1hAPIdMBYIRvc7D0w2zM15OnfuXCAixgVt\neSf1Mv7MrHJZ7MePH4P5lNofO8EanWu6W2t0cnIyjpcn4zxoM7pGbW2FwUFmZuHTp0+DYTInGWB8\nl/VWInNWVkOqL2Q2C3HdzHYc3aWlpZgZWfYlCkFbs7htZ0Xovn79GjO/Jzkof0tLmr0hB01FRx48\neDDQnJa3qMF3qZcQgdaMkAYH8urVqxFHpJF9Fk+Aa8rxh2YimGNjY6GJhO/9xCxsGADdvBc9jMV0\nOp1YWK/1hpVA3rI449iGCCOX/sSJE6EVMS8/MSDBGSiEsWFKZ8+ejQ4DVxrLcHzinhgLBPPZgkif\nPn2K86CNRn8bh3pp79C/Po/+v3v3bixo0OrCHrTPSobHH8FIZ2dnozuBzWFVmKDCCGl4Lruw1Pbt\n26PVC82dGzFlPsK/VSJzVlZDqi9kxuEF3GkZyLJ79+5YWCDeKAjhdbqHm0cPmoW63W4ETjjhNjDX\ndxM8ESvVy6M1OIjXrl2L9zdDlqGJeuljm925mpbKjY+Pr9qQ0PcUjuE8c43pb4i4a9eu6G/Si5gF\nVoPNQH3joB9pfJaWlgK1jA0vwpiU5XzQklxZMcTHjx8HmnJTsQrLPx0nNgB1Icvly5dXPZ/bNSPM\nIiRkCSe3H/oJfywvL4cvAZm9Zz2kpIR39LXpYhp9fn4+PAmegG4Idx4y2rZYFoIj/fz580BTzrrP\nxTA47bbrpZl9f0761NRUjLdrha52TtdbicxZWQ2pvpCZi0on6KFCqWPHjoX2ggwcwdqSw6qqeokZ\nOtdMdebMmZiRxERteCBeadteGscsDLEsgjh69Gg4wBJO0JarWi/Ou2PWd4bmMzMzq5xQaA7pIB+d\nCaG5+/fv3w8tjK2Y+XUCzNQ2StfLlCbjNv/48SMQgmaTEpPsKstnlhtNcLlv3LgR76n3b2M5Tjk0\np6ElATG1jRs3Rp9bP5lmpNE5xhxkfWWo7+fw8HA4xcZNZ4T2rRePwjmjNy3k2Lx5c7Ay38f15f0t\na+RRcPqxhSNHjsQ1Z/NHx2/8aWd6HKsSAzaGIyMj4Q3pLGCWa22L9KdKZM7Kakj1hczlZuQQknb5\n8uVLaDb9Qj1UKAvBOIQSWrLaExMT4SJ6f5qmXJKnP4cpcMjNaLOzszFT072QyMZqliNWVa/3xy3n\nCNeX5XFhHb+eJ+Yh1+zf3Et937m5uUBarIHTDl1pJp+rE0A7cmG/ffsW7i+m4HM8FqYs35FjD30x\nh9HR0dCUWJMcgfNhgz2LR8olkb9+/QodLR2G9egY+AyMSZfA63Trw4cPYzwsTcScJBLrxQXX98eu\nvF9V9bwKXRlekC6Kh8Ep1xU9f/369UBtDEwvGltwvUFungHW5Z4ZHh6OsfHdMTKu+norkTkrqyHV\nFzJzizm3Zj1a6c6dO+FS0h96j2Y77i+9Sy9CuAcPHkR2mdNpZoQMdAjE5lRiBbRcp9MJpxhSckRp\n23rRilxaPWPpqsXFxXCrrSDiblvBw2E3u2Ii9eSVv/F9jA3EgDyQG5JjL47h+PHjgRDQs1ylVBZ0\ng/I8BF2GrVu3BoroI3OaObJ6uI7TOTamCwsLgUyyAPrhPl+XQR6BTpTqksdvt9txfckkOE/8mXrp\nBPAM/K7r8vTp08EaMRwpRGzC+ecuY2Nc9FarFU44rayPjekZK4jtmuQz6RQsLCyEr0BHY1nyBeut\nROasrIZUX8hMH9AOEMJMfujQoZhRzW76bfVET1X1XEcrWPSZb926FTobMklrcQQhspnZrMhtv337\ndlVVfzMH6Ac1JMJoxHrRd/qp1tE6jkuXLoXWoevNsFiKvm+5lS/2MDAwEEjPRZUjNkPTntCczuQI\n6x7MzMxEok3vHXqvxTyqqpeawozoRtpudHQ0WIxxxp6gGxe49oifqqp6K4UGBwfjfXU1IJMeOw1b\n33y/qnrIVc8pc8vlzHkkPBTZ8KrqXaMYh343xF5cXIz/4yzr53PaIbHXOeLOy4YNG8LHcJ6NRfkY\nWK48Rxxjck1duXIlcgRYq/OcbnZW1v+0+kJmmsFOHJxh/d89e/aEzsX/rVc1A9M9HHE5ZPnnU6dO\nRe8R6nFVy21zIIHjgZb+/t69e4EA8sQQyXvVy2wKoWkpu6TcvHkzZme9Xjrd9/GIGeu06V368/Dh\nw7FhoDw6NDV2tLPf467TxZBxeXk5tDv32nv+k2bGjKT2yofUPXr0KPSevr3N+vVDIXG5rY1N875/\n/x7HXH8gYFX1zj9WB4UkqOhYaDg4OBhjLpugH2/bqHphFZxuaCvFNjExEdePzkOZF5f8Ms6SX66h\nquqxKuedr+BecG3ybPSooa/r4cKFC5E8k8LTR19rvfafqq+bmSBn4GjEu6nHxsZiwNn9zCwUWWPc\nRY7uohqTk5NBgyxNQ6Ptvllu52MQDJBBOH/+fNChclsXtL9e2khMLEsgtUa63W4Ye244LRA3CXrI\n+GLsqG63G20YZpWJQeuPjEFrtfVs3+Ni3LlzZ2zYwCTUGvmnJ1qIqrqZySFm1vT0dGwUIPBCAmnd\nGBd/y+xyE7RarWgfel/HZ4GC0AoazFx1E6Cn+/btC4rMtHPNrGUQMdhQVNTcDfnz58+4WexDLgjE\nhBV4EV5yAwqTPHv2LIInzq/FRq4L4+xcuWZ9L9JlamoqJk9j5cYHIuutpNlZWQ2pvpDZbFc3S+qv\nv3r1KmbtchkdysZ2R+tY+Z451Ol0Vj25Aq0zg5nFGUSQlFGG2rx8+XJV+wxCr7XzoTYPg8lSO5Rq\nx44dQc1QP4hspiYXHCO6BxnevHmzql2GEWh3eF2IAEUUeUXhP3z4EMEN6GXMjElZZn3tGVFN/+52\nuyGJmDpadM6tthuay4hk8m3bti0YAtYGTdFSr0M28sTxieS+ePEiWI7WkfEpWU99zDBBaOc6fPfu\nXbTSXGcMVzKBWeVckjdMxb1798Z3JoWgOoMUS8QmmJsWDTGKL168GOdAGwvjrG9quJ5KZM7Kakj1\nhcwQWYiclhBHW1lZWTWrlftj05jQCTJDus+fP4cmh3YQwKwNkZkqUJ/db+aem5uLYy6f/kgn1QuK\na6tAV8bfysrKqidQWvxAo/IK6EfIrP00MDAQoQuvMb78Lq0memkWF4BwPK9fv47fgQQMOTq2LK0h\n2h7KQ8yTJ0/GcYgTQhcmFcSGQv62/kQIDAxD045jQDofxo35ZDse11an04l2X/kEDd5KvZimQiNY\nBsPtyZMnwYAgNMOTESYUhRG53rUsh4aGgk3xADA2voZQjFCJzzLuzs/09HRsbGF/eG08ZuF6K5E5\nK6sh1Rcyi+aZZWlmzvD+/ftD65j9zNZmN06h2V/AQ1h/fn4+HFq6SpsC6tvo3azuKRLCBNoRb9++\njU0JaKZyuVu9RD057eW2NL9//46wi+8l5ADxLJqgpTnTWjBDQ0OBSpCFZqO/LGSAshxSnwkV3r9/\nHy0pmx/wLxxnWVC03M7IZ2/atCm0KFYlaFNuEgH9fDeoeODAgRhv14x2ksLmsCFtL+8lKNJut4Op\nOT9CNM53vQRdONVcZdfK+Ph4MDfHVIZSsATnEHuElO12O36XS208Xau+v9YrRMauMKpWqxXv5Xcw\nkbU2nfxTJTJnZTWk+no8TVZW1n+3EpmzshpSeTNnZTWk8mbOympI5c2cldWQyps5K6shlTdzVlZD\nKm/mrKyGVN7MWVkNqbyZs7IaUnkzZ2U1pP4CNkzcN/FWmn0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19ae62690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 250, D: 1.413, G:1.069\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQXqZExI6BOllTkjoEKSXOSGhQ/D/AM9rihhtZCdWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19ae2e310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 500, D: 1.32, G:0.9724\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197ef6110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 750, D: 1.329, G:0.5586\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nzB4eTQL/Mnt4NAn8y+zh0ST4f7cvpjGJI+MfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19abcf790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1000, D: 1.341, G:0.9498\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19aaabd50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1250, D: 1.325, G:0.8399\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBmZ2vL6yHwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff19782d350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1500, D: 1.295, G:0.8097\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJX8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1976a9490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n",
      "Iter: 1750, D: 1.307, G:0.7924\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPMAAADuCAYAAADsvjF6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nL7OHR5PAv8weHk0C/zJ7eDQJ/h824fPOmw0akwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff197415c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n"
     ]
    }
   ],
   "source": [
    "D_DC = build_dc_classifier().type(dtype) \n",
    "D_DC.apply(initialize_weights)\n",
    "G_DC = build_dc_generator().type(dtype)\n",
    "G_DC.apply(initialize_weights)\n",
    "\n",
    "D_DC_solver = get_optimizer(D_DC)\n",
    "G_DC_solver = get_optimizer(G_DC)\n",
    "\n",
    "run_a_gan(D_DC, G_DC, D_DC_solver, G_DC_solver, discriminator_loss, generator_loss, num_epochs=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# INLINE QUESTION 2\n",
    "What differences do you see between the DCGAN results and the original GAN results?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The digits look much smoother, less noisy. They look almost identical to the digits in the MNIST dataset. Using convolutional filters improved dramatically the performance of the network."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extra Credit \n",
    "** Be sure you don't destroy your results above, but feel free to copy+paste code to get results below **\n",
    "* For a small amount of extra credit, you can implement additional new GAN loss functions below, provided they converge. See AFI, BiGAN, Softmax GAN, Conditional GAN, InfoGAN, etc. \n",
    "* Likewise for an improved architecture or using a convolutional GAN (or even implement a VAE)\n",
    "* For a bigger chunk of extra credit, load the CIFAR10 data (see last assignment) and train a compelling generative model on CIFAR-10\n",
    "* Something new/cool.\n",
    "\n",
    "#### Describe what you did here\n",
    "** TBD **"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
